About NBDC Human Database
An enormous amount of human data is being generated with advances in next-generation sequencing and other analytical technologies. We therefore need rules and mechanisms for organizing and storing such data and for effectively utilizing them to make progress in the life sciences.
To promote sharing and utilization of human data while considering the protection of personal information, the Database Center for Life Science (DBCLS) of the Joint Support-Center for Data Science Research, Research Organization of Information and Systems (ROIS-DS) created a platform for sharing various data generated from human specimens, which are available for publicly access in cooperation with the DNA Data Bank of Japan
.
You can apply to use or submit human data through this website.
Violators of the guidelines who have not submitted a report on the deletion of Controlled-access data shall be disclosed here.
What's New
hum0014.v34
NBDC Research ID: hum0014.v34
SUMMARY
Aims: Identify disease-related genes and mobile element variations in Japanese
Methods: Genomic DNA samples were genotyped by following methods: Human610-Quad BeadChip, HumanHap550v3 Genotyping BeadChip, HumanOmniExpress-12 BeadChip, HumanExome BeadChip, OmniExpressExome BeadChip (Illumina), high-density oligonucleotide arrays (Perlegen Sciences), or Invader (Hologic Japan). Genome-Wide Association Studies (GWAS) for myocardial infarction (MI) , type II diabetes mellitus (T2DM), Atopic dermatitis (AD), atrial fibrillation (AF), Body Mass Index (BMI), primary open-angle glaucoma (POAG), 58 quantitative traits, age at menarche / menopause, smoking behaviour, height, 42 diseases (among them, the samples of 4 diseases were partially overlapped with those of previous release), dietary habits, and coronary artery disease were performed using about 500-2700K variants. Meta analyses for T2DM with diabetic nephropathy and for T2DM were also performed. SNP array analysis for 51 diseases registered in Biobank Japan were performed. Whole-genome sequencing analyses for 1,026 + 1,007 patients, who were registered Bio Bank Japan from 2003 - 2007, 1,765 myocardial infarction patients, 199 dementia patients, 256 + 2,067 gastric cancer patients, 617 colorectal cancer patients and 2,162 diabetes patients were performed with Illumina HiSeq 2500/X Five. Target sequencing analyses of 11 hereditary breast cancer genes in 7,104 breast cancer patients and 23,731 controls, 8 hereditary prostate cancer genes in 7,636 prostate cancer patients and 12,366 controls, 23 genes related to clonal hematopoiesis in 11,234 subjects extracted from approximately 200,000 subjects registered in Biobank Japan between fiscal years 2003 to 2007, 27 cancer-predisposing genes in 1,009 pancreatic cancer patients, 12,606 colorectal cancer patients, 740 renal cell cancer patients, 1,982 lymphoma patients, 10,366 gastric cancer patients and 23,780 + 5,996 + 37,592 controls and 13 renal cell carcinoma-related genes in 740 renal cell cancer patients and 5,996 controls were performed with Illumina HiSeq 2500. SNP array analysis for 11,234 subjects was also performed. A new reference panel was build with WGS data of the biobank Japan project (N=1,037) and the 1KGP p3v5 ALL (N=2,504). Sex-stratified genome-wide association studies using a Cox proportional hazard model under the assumption of the additive genetic model were performed. Associations of genetic variants estimated by saddle point estimation using SPACox software were also evaluated. A mobile element variation (MEV) search tool, MEGAnE, was applied to 4,880 WGS conducted in BBJ and 24,933 MEVs were found. Genome-wide association study for atrial fibrillation was performed in 9,826 cases and 140,446 controls. A subsequent cross-ancestry meta-analysis with European GWAS (60,620 cases and 970,216 controls; http://csg.sph.umich.edu/willer/public/afib2018) and Finnish GWAS (7,244 cases and 56,378 controls; FinnGenn; https://www.finngen.fi/en) was performed (77,690 cases and 1,167,040 controls in total). Polygenic risk score was constructed based on the cross-ancestry meta-analysis of atrial fibrillation.
Participants/Materials: Participants for the Tailor-made Medical Treatment Program (BioBank Japan: BBJ)
URL: https://biobankjp.org/cohort_3rd/english/index.html
| Dataset ID | Type of Data | Criteria | Release Date |
|---|---|---|---|
| hum0014.v1.freq.v1 | GWAS for MI | Unrestricted-access | 2014/09/30 |
| hum0014.v2.jsnp.934ctrl.v1 |
Genotype frequencies in 934 healthy individuals (JSNP data) |
Unrestricted-access | 2015/12/28 |
| 35 Dieases |
Genotype frequencies in each disease (JSNP data) |
Unrestricted-access | 2015/12/28 |
| hum0014.v2.jsnp.182ec.v1 |
Genotype frequencies in 182 esophageal cancer patients (JSNP data) |
Unrestricted-access | 2015/12/28 |
| hum0014.v2.jsnp.92als.v1 |
Genotype frequencies in 92 amyotrophic lateral sclerosis (ALS) patients (JSNP data) |
Unrestricted-access | 2015/12/28 |
| hum0014.v3.T2DM-1.v1 | GWAS for T2DM [1] | Unrestricted-access | 2016/01/28 |
| hum0014.v3.T2DM-2.v1 | GWAS for T2DM [2] | Unrestricted-access | 2016/01/28 |
| hum0014.v4.AD.v1 | GWAS for AD | Unrestricted-access | 2016/02/02 |
| hum0014.v5.AF.v1 | GWAS for AF | Unrestricted-access | 2016/05/18 |
| JGAS000101 | Genotype and phenotype data for 8180 AF patients | Controlled-access (Type I) | 2016/05/18 |
| hum0014.v6.158k.v1 | GWAS for BMI | Unrestricted-access | 2017/09/08 |
| JGAS000114 |
BMI data for 158,284 individuals Genotype data for 182,505 individuals |
Controlled-access (Type I) | 2017/09/08 |
| hum0014.v7.POAG.v1 | GWAS for POAG | Unrestricted-access | 2018/04/04 |
| hum0014.v8.58qt.v1 | GWAS for 58 quantitative traits | Unrestricted-access | 2018/05/01 |
| JGAS000114 | 58 quantitative traits data for 200,849 individuals | Controlled-access (Type I) | 2018/05/01 |
| GWAS for age at menarche and menopause | Unrestricted-access | 2018/08/07 | |
| JGAS000114 | WGS for 1,026 individuals | Controlled-access (Type I) | 2018/08/13 |
| JGAS000140 | target sequencing of 11 hereditary breast cancer genes in 7,104 breast cancer patients and 23,731 controls | Controlled-access (Type I) | 2018/10/16 |
| hum0014.v12.T2DMwN.v1 | meta analysis of 2 GWASs for T2DM with diabetic nephropathy | Unrestricted-access | 2018/12/10 |
| hum0014.v13.T2DMmeta.v1 | meta analysis of 4 GWASs for T2DM | Unrestricted-access | 2019/01/25 |
| hum0014.v14.smok.v1 | GWAS for smoking behaviour | Unrestricted-access | 2019/03/26 |
| JGAS000114 | a reference panel from WGS data of the biobank Japan project (N=1,037) and 1KGP p3v5 ALL (N=2,504) | Controlled-access (Type I) | 2019/09/27 |
| hum0014.v15.ht.v1 | GWAS for height | Unrestricted-access | 2019/09/27 |
| JGAS000203 | target sequencing of 8 hereditary prostate cancer genes in 7,636 prostate cancer patients and 12,366 controls | Controlled-access (Type I) | 2019/10/07 |
| hum0014.v17 | GWAS for 40 diseases | Unrestricted-access | 2019/10/08 |
| hum0014.v18 | GWAS for Breast cancer | Unrestricted-access | 2019/11/26 |
| hum0014.v19 | GWAS for dietary habits | Unrestricted-access | 2020/04/20 |
| hum0014.v20.cad.v1 | GWAS for coronary artery disease | Unrestricted-access | 2020/08/17 |
| hum0014.v21 | GWAS for coronary artery disease | Unrestricted-access | 2020/08/25 |
| JGAS000293 | target sequencing of 23 genes related to clonal hematopoiesis and SNP array in 11,234 subjects extracted from approximately 200,000 subjects registered in Biobank Japan between fiscal years 2003 to 2007 | Controlled-access (Type I) | 2021/05/21 |
| JGAS000114 (Data addition) | bam/gvcf data of WGS (JGAD000220) | Controlled-access (Type I) | 2021/07/13 |
| JGAS000327 | target sequencing of 27 cancer-predisposing genes in 1,005 pancreatic cancer patients | Controlled-access (Type I) | 2021/11/26 |
| JGAS000346 | target sequencing of 27 cancer-predisposing genes in 12,503 colorectal cancer patients and 23,705 controls | Controlled-access (Type I) | 2021/11/26 |
| JGAS000381 | WGS for 1,765 myocardial infarction patients and 199 dementia patients | Controlled-access (Type I) | 2022/01/25 |
| JGAS000414 | target sequencings of 27 cancer-predisposing genes and 13 renal cell carcinoma-related genes in 740 renal cell cancer patients and 5,996 controls | Controlled-access (Type I) | 2022/04/01 |
| hum0014.v27.surv.v1 | GWAS for survival time in 137,693 individuals from BBJ 1st cohort | Unrestricted-access | 2022/12/31 |
| hum0014.v28.MEs.v1 | mobile element variations in 4,880 individuals from BBJ 1st cohort | Unrestricted-access | 2023/04/05 |
| hum0014.v29.AF.v1 |
GWAS for 9,826 AF patients and 140,446 controls from BBJ 1st cohort GWAS meta-analysis for 77,690 AF patients and 1,167,040 controls |
Unrestricted-access | 2023/04/05 |
| JGAS000347 | target sequencing of 27 cancer-predisposing genes in 1,982 lymphoma patients | Controlled-access (Type I) | 2023/04/20 |
| JGAS000592 | target sequencing of 27 cancer-predisposing genes in 10,366 gastric cancer patients | Controlled-access (Type I) | 2023/04/20 |
| JGAS000592 | target sequencing of 27 cancer-predisposing genes in 37,592 controls | Controlled-access (Type I) | 2023/04/20 |
| JGAD000690 | Processed data of JGAD000220 (WGS for 1,026 individuals) by JGA (CRAM, gVCF) | Controlled-access (Type I) | 2023/08/31 |
| JGAD000758 | Processed data (joint call) of JGAD000220 (WGS for 1,026 individuals) by JGA (aggregate VCF) | Controlled-access (Type I) | 2023/08/31 |
| JGAD000679 | Processed data of JGAD000220 (reference panel) by JGA (data for the TogoImputation reference panel) | Controlled-access (Type I) | 2023/09/01 |
| JGAS000647 | WGS for 1,007 individuals | Controlled-access (Type I) | 2024/01/11 |
| JGAS000698 | WGS for 256 gastric cancer patients | Controlled-access (Type I) | 2024/05/27 |
| JGAS000703 | SNP array for 269,000 patients (51 diseases) in BBJ 1st and 2nd cohort | Controlled-access (Type I) | 2024/05/27 |
| JGAS000699 | WGS for 617 colorectal cancer patients | Controlled-access (Type I) | 2024/05/27 |
| JGAS000700 | low-depth WGS for 2,162 diabetes patients | Controlled-access (Type I) | 2024/05/27 |
| JGAS000701 | low-depth WGS for 2,067 gastric cancer patients | Controlled-access (Type I) | 2024/05/27 |
| JGAD000867 | Processed data of JGAD000220 (reference panel) by JGA (data for the TogoImputation reference panel) | Controlled-access (Type I) | 2024/09/19 |
| JGAD000868 | Processed data of JGAD000495 (reference panel) by JGA (data for the TogoImputation reference panel) | Controlled-access (Type I) | 2024/09/19 |
*Data users need to apply an application for Using NBDC Human Data to reach the Controlled-access Data. Learn more
* When the research results including the data which were downloaded from NHA/DRA, are published or presented somewhere, the data user must refer the papers which are related to the data, or include in the acknowledgment. Learn more
MOLECULAR DATA
| Participants/Materials | 1666 MI patients and 3198 controls |
| Targets | genome wide SNVs |
| Target Loci for Capture Methods | - |
| Platform | Illumina [Human610-Quad BeadChip, HumanHap550v3 Genotyping BeadChip] |
| Source | gDNA extracted from peripheral blood cells |
| Cell Lines | - |
| Reagents (Kit, Version) | Illumina Human610-Quad Beadchip |
| Genotype Call Methods (software) | GenCall software (GenomeStudio) |
| Filtering Methods | sample call rate ≧ 0.98, SNP call rate ≧ 0.99, HWE P ≧ 1 x 10^-6 |
| Marker Number (after QC) | 455,781 SNPs (hg18/GRCh36) |
| NBDC Dataset ID |
(Click the Dataset ID to download the file) |
| Total Data Volume | 71.3 MB (xlsx) |
| Comments (Policies) | NBDC policy |
| Participants/Materials | 934 Japanese healthy individuals (JSNP) |
| Targets | genome wide SNVs |
| Target Loci for Capture Methods | - |
| Platform | Illumina [HumanHap550v3 Genotyping BeadChip] |
| Source | gDNA extracted from peripheral blood cells |
| Cell Lines | - |
| Reagents (Kit, Version) | Illumina HumanHap550v3 Genotyping BeadChip |
| Genotype Call Methods (software) | GenCall software (GenomeStudio) |
| Filtering Methods | sample call rate < 0.98, SNP call rate < 0.99, HWE P < 1 x 10^-6 |
| Marker Number (after QC) | 515,286 SNPs |
| NBDC Dataset ID |
(Click the Dataset ID to download the file) |
| Total Data Volume | 32.2 M (zip [xls]) |
| Comments (Policies) | NBDC policy |
35 Diseases (JSNP)
| Participants/Materials |
Cancer (Lung cancer, Breast cancer, Gastric cancer, Colorectal cancer, Prostate cancer) Cardiovascular diseases (Heart failure, Myocardial infarction, Unstable angina, Stable angina, Cardiac arrhythmias, Arteriosclerosis obliterans) Cerebrovascular disorders (Brain infarction, Intracranial aneurysm) Respiratory tract diseases (Interstitial pneumonitis & pulmonary fibrosis, Pulmonary emphysema, Bronchial asthma) Chronic liver diseases (Chronic hepatitis C, Liver cirrhosis) Eye diseases (Cataract, Glaucoma) Others (Epilepsy, Periodontal disease, Urolithiasis, Nephrotic syndrome, Uterine myoma, Endometriosis, Osteoporosis, Rheumatoid arthritis, Amyotrophic lateral sclerosis, Hay fever, Atopic dermatitis, Drug eruptions , Hyperlipidemias, Diabetes mellitus, Basedow disease )
about 190 patients in each disease set |
| Targets | genome wide SNVs |
| Target Loci for Capture Methods | - |
| Platform | Perlegen Sciences [high-density oligonucleotide arrays] |
| Source | gDNA extracted from peripheral blood cells |
| Cell Lines | - |
| Reagents (Kit, Version) | - |
| Genotype Call Methods (software) | - |
| Filtering Methods | - |
| Marker Number (after QC) | About 200,000 SNPs (b129) |
| NBDC Dataset ID |
Cancer (Lung cancer, Breast cancer, Gastric cancer, Colorectal cancer, Prostate cancer) Cardiovascular diseases (Heart failure, Myocardial infarction, Unstable angina, Stable angina, Cardiac arrhythmias, Arteriosclerosis obliterans) Cerebrovascular disorders (Brain infarction, Intracranial aneurysm) Respiratory tract diseases (Interstitial pneumonitis & pulmonary fibrosis, Pulmonary emphysema, Bronchial asthma) Chronic liver diseases (Chronic hepatitis C, Liver cirrhosis) Eye diseases (Cataract, Glaucoma) Others (Epilepsy, Periodontal disease, Urolithiasis, Nephrotic syndrome, Uterine myoma, Endometriosis, Osteoporosis, Rheumatoid arthritis, Amyotrophic lateral sclerosis, Hay fever, Atopic dermatitis, Drug eruptions, Hyperlipidemias, Diabetes mellitus, Basedow disease) (Click the disease names to download the file) |
| Comments (Policies) | NBDC policy |
*Chromosomal position of each SNP is based on dbSNP build 129. If you need other mapping information, please contact us.
| Participants/Materials | 182 esophageal cancer patients (JSNP) |
| Targets | genome wide SNVs |
| Target Loci for Capture Methods | - |
| Platform | Illumina [HumanHap550v3 Genotyping BeadChip] |
| Source | gDNA extracted from peripheral blood cells |
| Cell Lines | - |
| Reagents (Kit, Version) | Illumina HumanHap550v3 Genotyping BeadChip |
| Genotype Call Methods (software) | GenCall software (GenomeStudio) |
| Filtering Methods | sample call rate < 0.98, SNP call rate < 0.99, HWE P < 1 x 10^-6 |
| Marker Number (after QC) | 503,734 SNPs |
| NBDC Dataset ID |
(Click the Dataset ID to download the file) |
| Total Data Volume | 6.6 MB (zip [txt]) |
| Comments (Policies) | NBDC policy |
| Participants/Materials | 92 ALS patients (JSNP) |
| Targets | large-scale case-control association study |
| Target Loci for Capture Methods | - |
| Platform | Hologic Japan [Invader] |
| Source | gDNA extracted from peripheral blood cells |
| Cell Lines | - |
| Reagents (Kit, Version) | Invader assay system (Third Wave Technologies) |
| Genotype Call Methods (software) | ABI PRISM SDS versions 2.0 - 2.2 |
| Filtering Methods | SNP call rate ≥ 0.95, HWE P ≥1.0 x 10^-2 |
| Marker Number (after QC) | 48,939 SNPs |
| NBDC Dataset ID |
(Click the Dataset ID to download the file) |
| Total Data Volume | 3.2 MB (zip [txt]) |
| Comments (Policies) | NBDC policy |
| Participants/Materials |
9817 T2DM patients 6763 controls (healthy individuals and patients with Intracranial aneurysm, Esophageal cancer, Uterine cancer, Pulmonary emphysema, or Glaucoma [without T2DM]) |
| Targets | genome wide SNVs |
| Target Loci for Capture Methods | - |
| Platform | Illumina [OmniExpressExome Beadchip] |
| Source | gDNA extracted from peripheral blood cells |
| Cell Lines | - |
| Reagents (Kit, Version) | Illumina OmniExpressExome Beadchip kit |
| Genotype Call Methods (software) | GenCall software (GenomeStudio) |
| Filtering Methods | sample call rate < 0.98, SNP call rate < 0.99, MAF < 0.01, HWE P < 1 x 10^-6 in control |
| Marker Number (after QC) | 552,915 SNPs (hg19) |
| NBDC Dataset ID |
(Click the Dataset ID to download the file) |
| Total Data Volume | 84.0 MB (xlsx) |
| Comments (Policies) | NBDC policy |
| Participants/Materials |
5646 T2DM patients 19,420 controls (patients with Colorectal cancer, Breast cancer, Prostate cancer, Lung cancer, Gastric cancer, Arteriosclerosis obliterans, Cardiac arrhythmias, Brain infarction, Myocardial infarction, Gallbladder cancer and Cholangiocarcinoma, Pancreatic cancer, Drug eruptions, Rheumatoid arthritis, Amyotrophic lateral sclerosis, Liver cancer, Liver cirrhosis, Osteoporosis, or Uterine myoma [without T2DM]) |
| Targets | genome wide SNVs |
| Target Loci for Capture Methods | - |
| Platform | Illumina [Human610-Quad BeadChip] |
| Source | gDNA extracted from peripheral blood cells |
| Cell Lines | - |
| Reagents (Kit, Version) | Illumina Human610-Quad Beadchip kit |
| Genotype Call Methods (software) | GenCall software (GenomeStudio) |
| Filtering Methods | sample call rate < 0.98, SNP call rate < 0.99, MAF < 0.01, HWE P < 1 x 10^-6 in control |
| Marker Number (after QC) | 479,088 SNPs (hg18) |
| NBDC Dataset ID |
(Click the Dataset ID to download the file) |
| Total Data Volume | 72.6 MB (xlsx) |
| Comments (Policies) | NBDC policy |
| Participants/Materials |
1472 AD patients 7966 controls (healthy individuals and patients with Intracranial aneurysm, Esophageal cancer, Uterine cancer, Pulmonary emphysema, or Glaucoma [without AD and Bronchial asthma]) |
| Targets | genome wide SNVs |
| Target Loci for Capture Methods | - |
| Platform | Illumina [HumanOmniExpress BeadChip] |
| Source | gDNA extracted from peripheral blood cells |
| Cell Lines | - |
| Reagents (Kit, Version) | HumanOmniExpress BeadChip |
| Genotype Call Methods (software) |
minimac [imputation (1000 genomes Phase I v3)] |
| Association Analysis (software) | mach2dat [GWAS] |
| Filtering Methods |
Genotyping QC: sample call rate < 0.98, SNV call rate < 0.99, HWE P < 1 x 10^-6 in the control samples Imputation QC: HWE P < 1 x 10^-6 or MAF < 0.01 in the reference panel Differences of MAF between the GWAS dataset and the reference panel > 0.16 |
| Marker Number (after QC) | About 7,700,000 SNPs (hg19) |
| NBDC Dataset ID |
(Click the Dataset ID to download the file) |
| Total Data Volume |
ADGWAS_auto.txt (525 MB) ADGWAS_X_females.txt (17 MB) ADGWAS_X_males.txt (15 MB) |
| Comments (Policies) | NBDC policy |
| Participants/Materials |
8180 atrial fibrillation patients and 28,612 controls |
| Targets | genome wide SNVs |
| Target Loci for Capture Methods | - |
| Platform | Illumina [HumanOmniExpress, HumanExome, OmniExpressExome BeadChip] |
| Source | DNA extracted from peripheral blood cells |
| Cell Lines | - |
| Reagents (Kit, Version) | HumanOmniExpress, HumanExome, OmniExpressExome BeadChip kit |
| Genotype Call Methods (software) |
minimac [imputation (1000 genomes Phase I v3)] GenCall software（GenomeStudio） |
| Association Analysis (software) | mach2dat [GWAS] |
| Filtering Methods |
Genotyping QC: sample call rate < 0.98, SNV call rate < 0.99, HWE P < 1 x 10^-6 in the control samples Imputation QC: HWE P < 1 x 10^-6 or MAF < 0.01 in the reference panel Differences of MAF between the GWAS dataset and the reference panel > 0.16 R square < 0.9 |
| Marker Number (after QC) | About 5,000,000 SNVs |
| Phenotype Data | Gender, Age |
|
NBDC Dataset ID / Japanese Genotype-phenotype Archive Dataset ID |
[GWAS stats] (Click the Dataset ID to download the file) [Individual datasets] Phenotype: JGAD000101 Genotype: JGAD000102 |
| Total Data Volume |
GWAS: 473 MB (txt) Individual phenotype-genotype data: 1 GB (txt) |
| Comments (Policies) | NBDC policy |
JGAS000114 / hum0014.v6.158k.v1
| Participants/Materials | 182,505 individuals (158,284 individuals for BMI study) |
| Targets | genome wide SNVs |
| Target Loci for Capture Methods | - |
| Platform | Illumina [HumanOmniExpress, HumanExome, OmniExpressExome BeadChip] |
| Source | DNA extracted from peripheral blood cells |
| Cell Lines | - |
| Reagents (Kit, Version) | HumanOmniExpress, HumanExome, OmniExpressExome BeadChip kit |
| Genotype Call Methods (software) |
minimac [imputation (1000 genomes Phase I v3)] GenCall software (GenomeStudio) |
| Association Analysis (software) | mach2qtl (v1.1.3) |
| Filtering Methods |
Genotyping QC: sample call rate < 0.98, SNV call rate < 0.99, HWE P < 1 x 10^-6 QC for reference panel: After excluding 11 closely related individuals, variants with HWE P < 1.0 x 10^-6, MAF < 0.01 were excluded. QC after imputation: Variants with imputation quality of Rsq < 0.7 were excluded. |
| Marker Number (after QC) | About 6,000,000 and 150,000 SNVs on autosomes and X-chromosome, respectively. |
|
NBDC Dataset ID / Japanese Genotype-phenotype Archive Dataset ID |
[GWAS] (Click the Dataset ID to download the file) [Individual datasets] Phenotype data (BMI): JGAD000124 Genotype data: JGAD000123 |
| Total Data Volume |
GWAS: 406 MB (zip) Phenotype data (BMI): 3.32 MB (txt.gz) Genotype data: 26.3GB (csv.gz) |
| Comments (Policies) | NBDC policy |
| Participants/Materials |
3980 POAG patients (Male: 1,997, Female: 1,983) 18,815 controls (Male: 7,817, Female: 10,998) |
| Targets | genome wide SNVs |
| Target Loci for Capture Methods | - |
| Platform | Illumina [HumanOmniExpress, HumanExome, OmniExpressExome BeadChip] |
| Source | gDNA extracted from peripheral blood cells |
| Cell Lines | - |
| Reagents (Kit, Version) | HumanOmniExpress, HumanExome, OmniExpressExome BeadChip kit |
| Genotype Call Methods (software) |
minimac（ver. 0.1.1） [imputation (1000 genomes Phase I v3)] |
| Association Analysis (software) | mach2dat（ver. 1.0.19） |
| Filtering Methods |
Genotyping QC: sample call rate < 0.98, SNV call rate < 0.99, HWE P < 1 x 10^-6 QC for reference panel: After excluding 11 closely related individuals, variants with HWE P < 1.0 x 10^-6, MAF < 0.01 were excluded. QC after imputation: Variants with imputation quality of Rsq < 0.7 were excluded. We also excluded variants with |beta| > 4 in the uploaded files. |
| Marker Number (after QC) |
autosomes: 5,961,428 SNPs (hg19) male X-chromosome: 147,351 SNPs (hg19) female X-chromosome: 147,353 SNPs (hg19) |
| NBDC Dataset ID |
(Click the Dataset ID to download the file) |
| Total Data Volume | 113 MB (txt.zip) |
| Comments (Policies) | NBDC policy |
JGAS000114 / hum0014.v8.58qt.v1
hum0014.v9.Men.v1 / hum0014.v9.MP.v1
| Participants/Materials |
67,029 females with information on age at menarche 43,861 females with information on age at menopause |
| Targets | genome wide SNVs |
| Target Loci for Capture Methods | - |
| Platform | Illumina [HumanOmniExpress, HumanExome, OmniExpressExome BeadChip] |
| Source | gDNA extracted from peripheral blood cells |
| Cell Lines | - |
| Reagents (Kit, Version) | HumanOmniExpress, HumanExome, OmniExpressExome BeadChip kit |
| Genotype Call Methods (software) |
minimac [imputation (1000 genomes Phase I v3)] GenCall software (GenomeStudio) |
| Association Analysis (software) | mach2qtl (v1.1.3) |
| Filtering Methods |
Genotyping QC: sample call rate < 0.98, SNV call rate < 0.99, HWE P < 1 x 10^-6 QC for reference panel: After excluding 11 closely related individuals, variants with HWE P < 1.0 x 10^-6, MAF < 0.01 were excluded. QC after imputation: Variants with imputation quality of Rsq < 0.7 were excluded. We also excluded variants with |beta| > 4 in the uploaded files. |
| Marker Number (after QC) | 9,296,729 SNPs (hg19) |
| NBDC Dataset ID |
menarche: hum0014.v9.Men.v1 menopause: hum0014.v9.MP.v1 (Click the Dataset ID to download the file) menarche: Dictionary file menopause: Dictionary file |
| Total Data Volume |
menarche: 181 MB (txt.gz) menopause: 186 MB (txt.gz) |
| Comments (Policies) | NBDC policy |
JGAS000114 (JGAD000220 / JGAD000410 / JGAD000690 / JGAD000758)
| Participants/Materials | 1,026 individuals |
| Targets | WGS |
| Target Loci for Capture Methods | - |
| Platform | Illumina [HiSeq 2500] |
| Library Source | DNA extracted from peripheral blood cells |
| Cell Lines | - |
| Library Construction (kit name) | TruSeq Nano DNA Library Preparation Kit |
| Fragmentation Methods | Ultrasonic fragmentation |
| Spot Type | Paired-end |
| Read Length (without Barcodes, Adaptors, Primers, and Linkers) | 160 bp |
| QC |
Data with bad base quality and high %GC content were removed. Alignment: Data matched for the following conditions were removed. - Low mapping rate - Different insert size - Gender information mismatch between meta-data and genotype data - Suspected sex chromosome aberration Genotyping: GATK’s best practices include a variant filtering step following Variant Quality Score Recalibration (VQSR) - DP/GP (DP < 5, GQ < 20, DP > 60, GQ < 95 ) - Heterozygosity (F>=0.05) - Hardy-Weinberg equilibrium (p < 10^-6） - Repeat & Low Complexity Principal Component Analysis (PCA): PCA was performed with individuals included in the 1000 genomes project and outliers from Japanese cluster were removed.
After these filtering steps, variants located in the regions listed as the HighConfidenceRegion (Genome-In-A-Bottle project) were flagged. |
| Deduplication | Picard 2.10.6 |
| Calibration for re-alignment and base quality | GATK 3.7 |
| Mapping Methods | BWA mem 0.7.12 |
| Mapping Quality | Reads with MAPQ<20 were excluded at variant calling with GATK 3.7 HaplotypeCaller |
| Reference Genome Sequence | GRCh37/hg19 (hs37d5) |
| Coverage (Depth) | 31.8x |
| Detecting Methods for Variation | GATK 3.7 HaplotypeCaller |
| SNV Numbers (after QC) |
76,768,387 (Autosomal Chromosomes) 2,898,518 (X Chromosome) |
| INDEL Numbers (after QC) |
10,202,908 (Autosomal Chromosomes) 410,435 (X Chromosome) |
| Japanese Genotype-phenotype Archive Dataset ID |
JGAD000220 (fastq) JGAD000410 (bam, vcf): Whole genome sequencing analyzed data included in the JGAD000117 were mapped to the GRCh37 reference genome sequence, and variant detection was carried out using the GATK (Genome Analysis Toolkit) standards. This project is an initiative of the GEnome Medical Alliance Japan (GEM Japan, GEM-J). Lean more.. |
| Dataset ID of the Processed data by JGA |
JGAD000758 (joint call) |
| Total Data Volume |
JGAD000220: 73 TB (fastq) JGAD000410: 49 TB (bam, vcf) JGAD000690: 52.1 TB (bam, bai, vcf, document) JGAD000758: 203.8 GB (vcf_aggregate, tabix) |
| Comments (Policies) | NBDC policy |
* Summarized data is available at JENGER site.
| Participants/Materials | 7,104 breast cancer patients and 23,731 controls |
| Targets | Target Capture |
| Target Loci for Capture Methods | 11 hereditary breast cancer genes (ATM, BRCA1, BRCA2, CDH1, CHEK2, NBN, NF1, PALB2, PTEN, STK11, TP53) |
| Platform | Illumina [HiSeq 2500] |
| Library Source | DNA extracted from peripheral blood cells |
| Cell Lines | - |
| Library Construction (kit name) | 1st PCR was performed with 2X Platinum Multiplex PCR Master Mix (Thermo Fisher Scientific) to amplify the target region, followed by the 2nd PCR with 8-bp barcode and adapter sequences added using KAPA HiFi HotStart DNA Polymerase (KAPA) *1 |
| Fragmentation Methods | - |
| Spot Type | Paired-end |
| Read Length (without Barcodes, Adaptors, Primers, and Linkers) | 150 bp x 2 |
| Japanese Genotype-phenotype Archive Dataset ID | JGAD000209 |
| Total Data Volume | 1 TB (fastq) |
| Comments (Policies) | NBDC policy |
*1 Hum Mol Genet. 25,:5027-5034 (2016)
| Participants/Materials |
[GWAS-1] - 2,380 T2DM with diabetic nephropathy patients - 5,234 T2DM without diabetic nephropathy patients [GWAS-2] - 429 T2DM with diabetic nephropathy patients - 358 T2DM without diabetic nephropathy patients |
| Targets | genome wide SNVs |
| Target Loci for Capture Methods | - |
| Platform | Illumina [OmniExpressExome Beadchip, Human610-Quad BeadChip] |
| Source | gDNA extracted from peripheral blood cells |
| Cell Lines | - |
| Reagents (Kit, Version) |
Illumina OmniExpressExome Beadchip kit Illumina Human610-Quad Beadchip kit |
| Genotype Call Methods (software) |
MACH and Minimac (1000 Genomes phased JPT, CHB and Han Chinese South data n = 275, March 2012) GenCall software (GenomeStudio) |
| Association Analysis (software) | mach2dat |
| Filtering Methods |
sample call rate < 0.98, SNV call rate < 0.99, MAF < 0.1%, HWE P < 1 x 10-6 in control |
| Marker Number (after QC) | 7,521,072 SNPs (hg19) |
| NBDC Dataset ID |
(Click the Dataset ID to download the file) |
| Total Data Volume | 310 MB (csv.zip) |
| Comments (Policies) | NBDC policy |
| Participants/Materials |
[GWAS-1] - 9,804 T2DM patients (ICD-10: E11) - 6,728 controls [GWAS-2] - 5,639 T2DM patients (ICD-10: E11) - 19,407 controls [GWAS-3] - 18,688 T2DM patients (ICD-10: E11) - 121,950 controls [GWAS-4] - 2,483 T2DM patients (ICD-10: E11) - 7,065 controls |
| Targets | genome wide SNVs |
| Target Loci for Capture Methods | - |
| Platform | Illumina [HumanOmniExpress, HumanExome, OmniExpressExome, Human610-Quad BeadChip] |
| Source | gDNA extracted from peripheral blood cells |
| Cell Lines | - |
| Reagents (Kit, Version) | HumanOmniExpress, HumanExome, OmniExpressExome, Human610-Quad BeadChip kit |
| Genotype Call Methods (software) |
minimac [imputation(1000 genomes Phase 3)] GenCall software (GenomeStudio) |
| Association Analysis (software) | mach2dat (v1.0.24) |
| Filtering Methods |
Genotyping QC: exclusion criteria of GWAS1, GWAS3, GWAS4 (i) hetero count < 5 (ii) HWE P < 1.0 × 10^-6 on each chip (iii) genotype concordance rate < 0.99 with in-house WGS data (iv) SNV call rate < 0.99
exclusion criteria of GWAS2 (i) SNV call rate < 0.99 (ii) MAF < 0.01 (iii) differential missingness P < 1.0 × 10^-6 (iv) HWE P < 1.0 × 10^-6
Imputation QC: HWE P < 1 × 10^-6 or MAF < 0.01 in the reference panel Imputation quality (Rsq) < 0.3 in more than two GWAS |
| Marker Number (after QC) | 12,557,761 SNPs (hg19) |
| NBDC Dataset ID |
(Click the Dataset ID to download the file) |
| Total Data Volume | 257 MB (txt) |
| Comments (Policies) | NBDC policy |
| Participants/Materials | 165,436 individuals whose smoking status is available |
| Targets | genome wide SNVs |
| Target Loci for Capture Methods | - |
| Platform | Illumina [HumanOmniExpress, HumanExome, OmniExpressExome BeadChip] |
| Source | gDNA extracted from peripheral blood cells |
| Cell Lines | - |
| Reagents (Kit, Version) | HumanOmniExpress, HumanExome, OmniExpressExome BeadChip kit |
| Genotype Call Methods (software) |
minimac [imputation (1000 genomes Phase I v3)] GenCall software (GenomeStudio) |
| Association Analysis (software) |
BOLT-LMM (v2.2) ProbABEL(v0.4.5; for X chromosome) |
| Filtering Methods |
Genotyping QC: sample call rate < 0.98, SNV call rate < 0.99, HWE P < 1 x 10^-6 QC for reference panel: After excluding 11 closely related individuals, variants with HWE P < 1.0 x 10^-6, MAF < 0.01 were excluded. QC after imputation: Variants with imputation quality of Rsq < 0.7 and MAF < 0.01 were excluded. |
| Marker Number (after QC) |
autosomes: 5,961,480 SNVs (hg19) male X-chromosome (Age of smoking initiation): 163,412 SNVs (hg19) female X-chromosome (Age of smoking initiation): 146,130 SNVs (hg19) male X-chromosome (Cigarettes per day): 166,111 SNVs (hg19) female X-chromosome (Cigarettes per day): 146,114 SNVs (hg19) male X-chromosome (Smoking initiation [Ever vs never smokers]): 166,138 SNVs (hg19) female X-chromosome (Smoking initiation [Ever vs never smokers]): 146,146 SNVs (hg19) male X-chromosome (Smoking cessation [Former vs current smokers]): 166,142 SNVs (hg19) female X-chromosome (Smoking cessation [Former vs current smokers]): 146,118 SNVs (hg19) |
| NBDC Dataset ID |
hum0014.v14.asi.v1.zip (Age of smoking initiation) hum0014.v14.cpd.v1.zip (Cigarettes per day) hum0014.v14.ens.v1.zip (Smoking initiation [Ever vs never smokers]) hum0014.v14.fcs.v1.zip (Smoking cessation [Former vs current smokers]) (Click the Dataset ID to download the file) |
| Total Data Volume | 1.9 GB (txt.gz) |
| Comments (Policies) | NBDC policy |
| Participants/Materials |
- WGS data (JGAD000220) of the biobank Japan project (N=1,037) - WGS data of 1KGP p3v5 ALL (N=2,504) (ftp://ftp.1000genomes.ebi.ac.uk/vol1/ftp/release/20130502/) |
| Targets |
a reference panel from WGS data (variants on autosomal chromosomes and X-chromosome) |
| Target Loci for Capture Methods | - |
| QC* |
We set exclusion criteria for genotypes as follows: (1) DP < 5, (2) GQ < 20, or (3) DP > 60 and GQ < 95, and regarded these genotypes as missing. Variants with call rates < 90% were excluded before variant quality score recalibration (VQSR). After VQSR, we excluded variants located in low-complexity regions (LCR), as defined by mdust software were excluded. Finally, we used BEAGLE to impute missing genotypes.
|
| Deduplication* | picard (versions 1.106) |
| Calibration for re-alignment and base quality* | GATK (ver.3.2-2) |
| Mapping Methods* | BWA-MEM (version 0.7.5a) |
| Mapping Quality* | MAPQ < 20 were excluded (HaplotypeCaller) |
| Reference Genome Sequence* | GRCh37/hg19, hs37d5 |
| Coverage (Depth)* | aimed at 30x depth |
| Detecting Methods for Variation* | GATK HaplotypeCaller (version 3.2-2) |
| Method for merging vcf files |
autosomal chromosomes: Impute2 X-chromosome: Beagle (male), Impute2 (female) |
| Variant Numbers in reference panel | 61,608,817 variants (autosomal chromosomes: 59,387,070; X-chromosome: 2,221,747) |
| Japanese Genotype-phenotype Archive Dataset ID | JGAD000220 |
| Dataset ID of the Processed data by JGA | |
| Total Data Volume | about 15 GB (vcf.gz) |
| Comments (Policies) | NBDC policy |
* These processes were performed only for biobank Japan project data.
| Participants/Materials | 159,095 individuals (Male: 86,257, Female: 72,838) |
| Targets | genome wide variants |
| Target Loci for Capture Methods | - |
| Platform | Illumina [HumanOmniExpress, HumanExome, OmniExpressExome BeadChip] |
| Source | gDNA extracted from peripheral blood cells |
| Cell Lines | - |
| Reagents (Kit, Version) | HumanOmniExpress, HumanExome, OmniExpressExome BeadChip kit |
| Genotype Call Methods (software) | Minimac3 [imputation reference panel using WGS data of the biobank Japan project (N=1,037) and 1KGP p3v5 ALL (N=2,504)] |
| Association Analysis (software) | BOLT-LMM (ver2.2), mach2qtl |
| Filtering Methods |
Sample QCs: Exclusion criteria: 1) call rate < 98%, 2) closely related samples (PI_HAT > 0.175), and 3) outlier from Japanese cluster determined by PCA using GCTA. QC after imputation: Variants with imputation quality of Rsq < 0.3 were excluded. |
| Marker Number (after QC) |
autosomes: 27,211,524 variants (hg19) male X-chromosome: 684,533 variants (hg19) female X-chromosome: 684,533 variants (hg19) |
| NBDC Dataset ID |
(Click the Dataset ID to download the file) |
| Total Data Volume | about 663 MB (txt.gz) |
| Comments (Policies) | NBDC policy |
| Participants/Materials | 7,636 prostate cancer patients (ICD10：C61) and 12,366 controls |
| Targets | Target Capture |
| Target Loci for Capture Methods | 8 hereditary prostate cancer genes (ATM, BRCA1, BRCA2, BRIP1, CHEK2, HOXB13, NBN, PALB2) |
| Platform | Illumina [HiSeq 2500] |
| Library Source | DNA extracted from peripheral blood cells |
| Cell Lines | - |
| Library Construction (kit name) | 1st PCR was performed with 2X Platinum Multiplex PCR Master Mix (Thermo Fisher Scientific) to amplify the target region, followed by the 2nd PCR with 8-bp barcode and adapter sequences added using KAPA HiFi HotStart DNA Polymerase (KAPA) *1 |
| Fragmentation Methods | - |
| Spot Type | Paired-end |
| Read Length (without Barcodes, Adaptors, Primers, and Linkers) | 150 bp x 2 |
| Japanese Genotype-phenotype Archive Dataset ID | JGAD000288 |
| Total Data Volume | 2.2 TB (fastq) |
| Comments (Policies) | NBDC policy |
hum0014.v17 / hum0014.v18 / hum0014.v21
| Participants/Materials |
42 disease (ICD10 code) Arrhythmia (I499), Bronchial asthma (J459), Atopic dermatitis (L209), Gallbladder/Cholangiocarcinoma (C23, C240), Cataract (H269), Cerebral aneurysm (I671), Cervical cancer (C539), Chronic hepatitis B (B181), Chronic hepatitis C (B182), Chronic obstructive pulmonary disease (J449), Liver cirrhosis (K746), Colorectal cancer (C189, C20), Heart failure (I509, I500), Drug eruption (L270), Uterine cancer (C549), Endometriosis (N809), Epilepsy (G409), Esophageal cancer (C159), Gastric cancer (C169), Glaucoma (H409), Graves' disease (E050), Hematopoietic tumor (C81-96), Liver cancer (C220), Interstitial lung disease/Pulmonary fibrosis (J849, J841), Cerebral infarction (I639), Keloid (L910), Lung cancer (C349), Nephrotic syndrome (N049), Osteoporosis (M8199), Ovarian cancer (C56), Pancreas cancer (C259), Periodontitis (K054), Peripheral artery disease (I709), Hay fever (J301), Prostate cancer (C61), Pulmonary tuberculosis (A169), Rheumatoid arthritis (M0690), Diabetes mellitus (E14), Urolithiasis (N209), Uterine fibroids (D259), Breast cancer (C509) Coronary artery disease (I200, I209, I219) |
|
| Targets | genome wide variants | |
| Target Loci for Capture Methods | - | |
| Platform | Illumina [HumanOmniExpress, HumanExome, OmniExpressExome BeadChip] | |
| Source | gDNA extracted from peripheral blood cells | |
| Cell Lines | - | |
| Reagents (Kit, Version) | HumanOmniExpress, HumanExome, OmniExpressExome BeadChip kit | |
| Genotype Call Methods (software) |
Minimac3 [imputation (1000 genomes Phase 3 v5)] GenCall software (GenomeStudio) |
|
| Association Analysis (software) | SAIGE(v0.29.4.2) | |
| Filtering Methods |
QC after imputation: Exclusion criteria: Variants with imputation quality of Rsq < 0.7 |
|
| Marker Number (after QC) |
autosomes: 8,712,794 variants (hg19) X-chromosome: 207,198 variants (hg19) |
|
| NBDC Dataset ID | Arrhythmia | hum0014.v17.AR.v1 |
| Bronchial asthma | hum0014.v17.BA.v1 | |
| Atopic dermatitis* | hum0014.v17.AD.v1 | |
| Gallbladder/Cholangiocarcinoma | hum0014.v17.GCc.v1 | |
| Cataract | hum0014.v17.Cat.v1 | |
| Cerebral aneurysm | hum0014.v17.CA.v1 | |
| Cervical cancer | hum0014.v17.CeC.v1 | |
| Chronic hepatitis B | hum0014.v17.CHB.v1 | |
| Chronic hepatitis C | hum0014.v17.CHC.v1 | |
| Chronic obstructive pulmonary disease | hum0014.v17.COPD.v1 | |
| Liver cirrhosis | hum0014.v17.Cir.v1 | |
| Colorectal cancer | hum0014.v17.CC.v1 | |
| Heart failure* | hum0014.v17.HF.v1 | |
| Drug eruption | hum0014.v17.DE.v1 | |
| Uterine cancer | hum0014.v17.UC.v1 | |
| Endometriosis | hum0014.v17.EM.v1 | |
| Epilepsy | hum0014.v17.Ep.v1 | |
| Esophageal cancer | hum0014.v17.EC.v1 | |
| Gastric cancer | hum0014.v17.GC.v1 | |
| Glaucoma* | hum0014.v17.Gla.v1 | |
| Graves' disease | hum0014.v17.GD.v1 | |
| Hematopoietic tumor | hum0014.v17.HT.v1 | |
| Liver cancer | hum0014.v17.LiC.v1 | |
| Interstitial lung disease/Pulmonary fibrosis | hum0014.v17.IP.v1 | |
| Cerebral infarction | hum0014.v17.CI.v1 | |
| Keloid | hum0014.v17.Kel.v1 | |
| Lung cancer | hum0014.v17.LuC.v1 | |
| Nephrotic syndrome | hum0014.v17.NS.v1 | |
| Osteoporosis | hum0014.v17.OP.v1 | |
| Ovarian cancer | hum0014.v17.OC.v1 | |
| Pancreas cancer | hum0014.v17.PaC.v1 | |
| Periodontitis | hum0014.v17.PD.v1 | |
| Peripheral artery disease | hum0014.v17.PAD.v1 | |
| Hay fever | hum0014.v17.Hay.v1 | |
| Prostate cancer | hum0014.v17.PrC.v1 | |
| Pulmonary tuberculosis | hum0014.v17.PT.v1 | |
| Rheumatoid arthritis | hum0014.v17.RA.v1 | |
| Diabetes mellitus* | hum0014.v17.DM.v1 | |
| Urolithiasis | hum0014.v17.Uro.v1 | |
| Uterine fibroids | hum0014.v17.UF.v1 | |
| Breast cancer | hum0014.v18.BC.v1 | |
| Coronary artery disease | hum0014.v21.CAD.v1 | |
|
(Click the Dataset ID to download the file) |
||
| Total Data Volume |
autosomes: about 0.8-1.3 GB each X-chromosome: about 20-30 MB each |
|
| Comments (Policies) | NBDC policy | |
* Data of 4 diseases were partially overlapped with those of previous releases (Glaucoma [hum0014.v7.POAG.v1], Atrial fibrillation [hum0014.v5.AF.v1], Atopic dermatitis [hum0014.v4.AD.v1], and Diabetes mellitus [hum0014.v3.T2DM-2.v1]).
| Participants/Materials | 165,084 individuals whose dietary habits status is available (13 dietary traits) | |
| Targets | genome wide SNVs | |
| Target Loci for Capture Methods | - | |
| Platform | Illumina [HumanOmniExpress, HumanExome, OmniExpressExome BeadChip] | |
| Source | gDNA extracted from peripheral blood cells | |
| Cell Lines | - | |
| Reagents (Kit, Version) | HumanOmniExpress, HumanExome, OmniExpressExome BeadChip kit | |
| Genotype Call Methods (software) |
GenCall software（GenomeStudio） MACH minimac (v.0.1.1) [imputation (1000 genomes Phase I v3)] |
|
| Association Analysis (software) |
BOLT-LMM (v2.2) for autosomes ProbABEL (v0.4.5) for X chromosome |
|
| Filtering Methods |
Genotyping QC: sample call rate < 0.98, SNV call rate < 0.99, MAF < 0.005 QC for reference panel: Variants with HWE P < 1.0 x 10^-6, MAF < 0.01 were excluded from the reference panel. QC after imputation: Variants with imputation quality of Rsq < 0.7 and MAF < 0.01 were excluded. |
|
| Marker Number (after QC) |
autosomes: 5,961,480 variants (hg19) X-chromosome: 148,568 variants for female, 170,117 variants for male (hg19) |
|
| NBDC Dataset ID | Ever versus never drinker | hum0014.v19.drink.v1.zip |
| Drinks per week | hum0014.v19.dpw.v1.zip | |
| Coffee consumption | hum0014.v19.cafe.v1.zip | |
| Tea consumption | hum0014.v19.tea.v1.zip | |
| Milk consumption | hum0014.v19.milk.v1.zip | |
| Yogurt consumption | hum0014.v19.ygt.v1.zip | |
| Cheese consumption | hum0014.v19.cheese.v1.zip | |
| Natto consumption | hum0014.v19.natto.v1.zip | |
| Tofu consumption | hum0014.v19.tofu.v1.zip | |
| Fish consumption | hum0014.v19.fish.v1.zip | |
| Small fish consumption | hum0014.v19.sfish.v1.zip | |
| Vegetable consumption | hum0014.v19.vege.v1.zip | |
| Meat consumption | hum0014.v19.meat.v1.zip | |
|
(Click the Dataset ID to download the file) |
||
| Total Data Volume | 6.3 GB (txt.zip) | |
| Comments (Policies) | NBDC policy | |
| Participants/Materials |
25,892 coronary artery disease patients (ICD10: I20-25) and 142,336 controls |
| Targets | genome wide variants |
| Target Loci for Capture Methods | - |
| Platform | Illumina [HumanOmniExpress, HumanExome, OmniExpressExome BeadChip] |
| Source | gDNA extracted from peripheral blood cells |
| Cell Lines | - |
| Reagents (Kit, Version) | HumanOmniExpress, HumanExome, OmniExpressExome BeadChip kit |
| Genotype Call Methods (software) |
GenCall software (GenomeStudio) minimac3 (BBJ-CAD reference panel) |
| Association Analysis (software) | PLINK2 |
| Filtering Methods | QC after imputation: Variants with imputation quality of Rsq < 0.3 and MAF < 0.0002 were excluded. |
| Marker Number (after QC) | autosomes: 19,707,525 variants (hg19) |
| NBDC Dataset ID |
hum0014.v20.gwas.v1 (summary statistics) hum0014.v20.prs.v1 (polygenic risk score) (Click the Dataset ID to download the file) |
| Total Data Volume | about 413 MB (txt.gz) |
| Comments (Policies) | NBDC policy |
| Participants/Materials | 11,234 subjects extracted from approximately 200,000 subjects registered in Biobank Japan between fiscal years 2003 to 2007 |
| Targets | Target Capture |
| Target Loci for Capture Methods |
23 genes related to clonal hematopoiesis ASXL1, CBL, CEBPA, DDX41, DNMT3A, ETV6, EZH2, GATA2, GNAS, GNB1, IDH1, IDH2, JAK2, KRAS, MYD88, NRAS, PPM1D, RUNX1, SF3B1, SRSF2, TET2, TP53, U2AF1 |
| Platform | Illumina [HiSeq 2500] |
| Library Source | DNA extracted from peripheral blood cells |
| Cell Lines | - |
| Library Construction (kit name) | Library was contructed as described in Momozawa, Y., et al. Low-frequency coding variants in CETP and CFB are associated with susceptibility of exudative age-related macular degeneration in the Japanese population. Hum Mol Genet 25, 5027-5034 (2016). |
| Fragmentation Methods | - |
| Spot Type | Paired-end |
| Read Length (without Barcodes, Adaptors, Primers, and Linkers) | 150 bp |
| QC | We selected samples in which ≥20 depth was achieved in ≥98% regions. |
| Mapping Methods | bwa |
| Mapping Quality | ≥40 |
| Reference Genome Sequence | hg19 |
| Coverage (Depth) | x800 |
| Detecting Methods for Variation | Genomon pipeline |
| Filtering Methods | Genomon pipeline |
| Japanese Genotype-phenotype Archive Dataset ID | JGAD000399 |
| Total Data Volume | 5.3 MB (txt) |
| Comments (Policies) | NBDC policy |
| Participants/Materials | 11,234 subjects extracted from approximately 200,000 subjects registered in Biobank Japan between fiscal years 2003 to 2007 |
| Targets | SNP array |
| Target Loci for Capture Methods | - |
| Platform | Illumina [human OmniExpress, human OmniExpressExome] |
| Library Source | DNA extracted from peripheral blood cells |
| Cell Lines | - |
| Reagents (Kit, Version) | Illumina Infinium OmniExpress, Infinium OmniExpressExome v.1.0, or v.1.2 |
| Genotype Call Methods (software) | GenCall software（GenomeStudio） |
| Algorithm for detecting chromosome abnormality (software) |
Haplotype-based detection of allelic imbalances. |
| Filtering Methods | SNPs examined in all of the three versions of array |
| Marker Numbers (after QC) | 515,355 |
| Japanese Genotype-phenotype Archive Dataset ID | JGAD000400 |
| Total Data Volume | 5.3 MB (csv) |
| Comments (Policies) | NBDC policy |
JGAS000327 / JGAS000346 / JGAS000414 / JGAS000347 / JGAS000592
| Participants/Materials |
1,005 pancreatic cancer patients (ICD10: C25) 12,503 colorectal cancer patients (ICD10: C18, C19, C20) 740 renal cell cancer patients (ICD10: C64) 1,982 lymphoma patients (ICD10: C81, C82, C83, C84, C85, C86, C88, C91) 10,366 gastric cancer patients (ICD10: C16) 23,705 + 5,996 + 37,592 controls |
| Targets | Target Capture |
| Target Loci for Capture Methods | 27 cancer-predisposing genes (APC, ATM, BARD1, BMPR1A, BRCA1, BRCA2, BRIP1, CDK4, CDKN2A, CDH1, CHEK2, EPCAM, HOXB13, NBN, NF1, MLH1, MSH2, MSH6, MUTYH, PALB2, PMS2, PTEN, RAD51C, RAD51D, SMAD4, STK11, TP53) |
| Platform | Illumina [HiSeq 2500] |
| Library Source | DNA extracted from peripheral blood cells |
| Cell Lines | - |
| Library Construction (kit name) | 1st PCR was performed with 2X Platinum Multiplex PCR Master Mix (Thermo Fisher Scientific) to amplify the target region, followed by the 2nd PCR with 8-bp barcode and adapter sequences added using KAPA HiFi HotStart DNA Polymerase (KAPA) *1 |
| Fragmentation Methods | - |
| Spot Type | Paired-end |
| Read Length (without Barcodes, Adaptors, Primers, and Linkers) | 150 bp x 2 |
| Japanese Genotype-phenotype Archive Dataset ID |
pancreatic cancer: JGAD000438 colorectal cancer: JGAD000458 23,705 controls: JGAD000459 renal cell cancer and 5,996 controls: JGAD000531 lymphoma: JGAD000460 gastric cancer: JGAD000720 37,592 controls: JGAD000721 |
| Total Data Volume |
JGAD000438: 78 GB (fastq) JGAD000458: 956 GB (fastq) JGAD000459: 1.9 TB (fastq) JGAD000531: 961.8 GB (fastq) JGAD000460: 126 GB (fastq) JGAD000720, JGAD000721: 3.4 TB (fastq) |
| Comments (Policies) | NBDC policy |
| Participants/Materials |
740 renal cell cancer patients (ICD10：C64) 5,996 controls |
| Targets | Target Capture |
| Target Loci for Capture Methods | 13 renal cell carcinoma-related genes (VHL, BAP1, FH, FLCN, MET, TSC1, TSC2, MITF, SDHA, SDHB, SDHC, SDHD, CDC73) |
| Platform | Illumina [HiSeq 2500] |
| Library Source | DNA extracted from peripheral blood cells |
| Cell Lines | - |
| Library Construction (kit name) | 1st PCR was performed with 2X Platinum Multiplex PCR Master Mix (Thermo Fisher Scientific) to amplify the target region, followed by the 2nd PCR with 8-bp barcode and adapter sequences added using KAPA HiFi HotStart DNA Polymerase (KAPA) *1 |
| Fragmentation Methods | - |
| Spot Type | Paired-end |
| Read Length (without Barcodes, Adaptors, Primers, and Linkers) | 150 bp x 2 |
| Japanese Genotype-phenotype Archive Dataset ID | JGAD000531 |
| Total Data Volume | JGAD000531: 961.8 GB (fastq) |
| Comments (Policies) | NBDC policy |
| Participants/Materials | 1,765 myocardial infarction patients (ICD10: I21) and 199 dementia patients (ICD10: F00-03) |
| Targets | WGS |
| Target Loci for Capture Methods | - |
| Platform | Illumina [HiSeq X Five] |
| Library Source | DNA extracted from peripheral blood cells |
| Cell Lines | - |
| Library Construction (kit name) | TruSeq DNA PCR-Free Prep kit |
| Fragmentation Methods | Ultrasonic fragmentation |
| Spot Type | Paired-end |
| Read Length (without Barcodes, Adaptors, Primers, and Linkers) | 151 bp |
| QC |
Data with bad base quality and high %GC content were removed. Aligment: Data matched for the following condition were removed. - Low mapping rate - Different insert size - Gender information mismatch between meta-data and genotype data - Suspected sex chromosome aberration Genotyping: GATK’s best practices includes a variant filtering step following Variant Quality Score Recalibration (VQSR) - DP/GP (DP < 5, GQ < 20, DP > 60, GQ < 95 ) - Heterozygosity (F>=0.05) - Hardy-Weinberg equilibrium (p < 10^-6） - Repeat & Low Complexity Principal Component Analysis (PCA): PCA was performed with individuals included in the 1000 genomes project and outliers from Japanese cluster were removed. After these filtering steps, variants located in the regions listed as the HighConfidenceRegion (Genome-In-A-Bottle project) were flagged. |
| Deduplication | Picard 2.10.6 |
| Calibration for re-alignment and base quality | GATK 3.7 |
| Mapping Methods | BWA mem 0.7.12 |
| Mapping Quality | Reads with MAPQ<20 were excluded at variant calling with GATK 3.7 HaplotypeCaller |
| Reference Genome Sequence | GRCh37/hg19 (hs37d5) |
| Coverage (Depth) | myocardial infarction: 15.0x, dementia: 30.0x |
| Detecting Methods for Variation | GATK 3.7 HaplotypeCaller |
| SNV Numbers (after QC) |
76,768,387 (Autosomal Chromosomes) 2,898,518 (X Chromosome) |
| INDEL Numbers (after QC) |
10,202,908 (Autosomal Chromosomes) 410,435 (X Chromosome) |
| Japanese Genotype-phenotype Archive Dataset ID |
JGAD000495 (fastq) JGAD000496 (bam, vcf): Whole genome sequencing analyzed data included in the JGAD000117 were mapped to the GRCh37 reference genome sequence, and variant detection was carried out using the GATK (Genome Analysis Toolkit) standards. This project is an initiative of the GEnome Medical alliance Japan (GEM Japan, GEM-J). Lean more.. |
| Total Data Volume | 188.4 TB (fastq, bam, vcf) |
| Comments (Policies) | NBDC policy |
| Participants/Materials |
137,693 individuals from BBJ 1st cohort |
| Targets | genome wide variants |
| Target Loci for Capture Methods | - |
| Platform | Illumina [HumanOmniExpress, HumanExome, OmniExpressExome BeadChip] |
| Source | gDNA extracted from peripheral blood cells |
| Cell Lines | - |
| Reagents (Kit, Version) | HumanOmniExpress, HumanExome, OmniExpressExome BeadChip kit |
| Genotype Call Methods (software) |
minimac [imputation (1000 genomes Phase I v3)] GenCall software (GenomeStudio) |
| Association Analysis (software) |
mach2qtl (v1.1.3) SPACox |
| Filtering Methods |
Genotyping QC: sample call rate < 0.98, SNV call rate < 0.99, HWE P < 1 x 10^-6 QC for reference panel: After excluding 11 closely related individuals, variants with HWE P < 1.0 x 10^-6, MAF < 0.01 were excluded. QC after imputation: Variants with imputation quality of Rsq < 0.7 were excluded. |
| Marker Number (after QC) | 6,108,833 variants (hg19) |
| NBDC Dataset ID |
(Click the Dataset ID to download the file) |
| Total Data Volume | 789 MB (txt.gz) |
| Comments (Policies) | NBDC policy |
| Participants/Materials |
WGS data of 4,880 individuals from BBJ 1st cohort - WGS data (JGAD000220) of the biobank Japan project (N=1,037) - WGS data (JGAD000495) of 1,765 myocardial infarction patients and 199 dementia patients - WGS data (AGDD_000005) of 225 gastric cancer patients - 1,007 individuals from Asian Genome Project - 617 colorectal cancer patients - One individual excluded from AGDD_000005 by QC - 10 individuals excluded from JGAD000220 by QC |
| Targets | mobile element variations |
| Target Loci for Capture Methods | - |
| Platform | Illumina [HiSeq X/2500] |
| Library Source | gDNA extracted from peripheral blood cells |
| Cell Lines | - |
| Library Construction (kit name) | TruSeq DNA PCR-Free Sample Prep Kit, TruSeq Nano DNA HT Sample Prep Kit |
| Fragmentation Methods | Ultrasonic fragmentation |
| Spot Type | Paired-end |
| Read Length (without Barcodes, Adaptors, Primers, and Linkers) | 151 bp (HiSeq X), 126 bp (HiSeq 2500) |
| QC | - |
| Mapping Methods | BWA-MEM |
| Mapping Quality | - |
| Reference Genome Sequence | GRCh37 (hs37d5) |
| Coverage (Depth) | ≥15× (≥25× for 1,235 individuals) |
| Detecting Methods for mobile element | MEGAnE *2 |
| Mobile element Number |
24,933 for 4,880 individuals 10,997 for 1,235 individuals |
| NBDC Dataset ID |
(Click the Dataset ID to download the file) |
| Total Data Volume | 1.1 MB (txt.gz) |
| Comments (Policies) | NBDC policy |
*2 doi: 10.1101/2022.03.25.485726
| Participants/Materials |
77,690 atrial fibrillation patients and 1,167,040 controls BBJ: 9,826 atrial fibrillation patients and 140,446 controls European: 60,620 atrial fibrillation patients and 970,216 controls FinnGen: 7,244 atrial fibrillation patients and 56,378 controls |
| Targets | genome wide SNVs |
| Target Loci for Capture Methods | - |
| Platform | Illumina [HumanOmniExpress、HumanExome、OmniExpressExome BeadChip] |
| Source |
DNA extracted from peripheral blood cells European GWAS: http://csg.sph.umich.edu/willer/public/afib2018 FinnGen GWAS: https://www.finngen.fi/en |
| Cell Lines | - |
| Reagents (Kit, Version) | HumanOmniExpress, HumanExome, OmniExpressExome BeadChip kit |
| Genotype Call Methods (software) |
GenCall software (GenomeStudio), minimac [imputation (1000 genomes Phase I v3 )] |
| Association Analysis (software) | PLINK2 |
| Filtering Methods |
BBJ GWAS: variants with imputation quality (Rsq) < 0.3 or MAF < 0.001 were excluded meta-analysis: variants with MAF < 1% were excluded |
| Calculation Methods for Polygenic Risk Score | runing and thresholding method |
| Meta Analysis Methods | MANTRA, METAL |
| Marker Number (after QC) |
BBJ GWAS: 16,817,144 SNPs meta-analysis : 5,158,449 SNPs |
| NBDC Dataset ID |
(Click the Dataset ID to download the file) |
| Total Data Volume |
summary statistics of BBJ: 424 MB (txt) summary statistics of meta analysis: 78 MB (txt) polygenic risk score: 59 KB (txt) |
| Comments (Policies) | NBDC policy |
| Participants/Materials | 1,007 individuals from BBJ 1st cohort |
| Targets | WGS |
| Target Loci for Capture Methods | - |
| Platform | Illumina [HiSeq X Five] |
| Library Source | DNA extracted from peripheral blood cells |
| Cell Lines | - |
| Library Construction (kit name) | TruSeq Nano DNA Library Preparation Kit |
| Fragmentation Methods | Ultrasonic fragmentation |
| Spot Type | Paired-end |
| Read Length (without Barcodes, Adaptors, Primers, and Linkers) | 150 bp |
| QC |
- Autosomal Chromosomes, X PAR, X NonPAR female - Set missing genotypes with DP < 2 or GQ < 20 - call rate < 90% were excluded - X NonPAR male, Y - Set missing genotypes with DP < 1 or GQ < 20 - call rate < 90% were excluded - X NomPAR HWE_P of female |
| Deduplication | Picard 2.10.10 |
| Calibration for re-alignment and base quality | GATK 3.8 |
| Mapping Methods | BWA-MEM (version 0.7.13) |
| Mapping Quality | Reads with MAPQ<20 were excluded at variant calling with GATK 3.8 HaplotypeCaller |
| Reference Genome Sequence | hs37d5 |
| Coverage (Depth) | 19.93455 |
| Detecting Methods for Variation | GATK Haplotype Caller (version 3.8) |
| SNV Numbers (after QC) |
Autosomal Chromosomes: 71,643,487 X PAR: 82,997 X nonPAR: 2,618,495 Y Chromosome: 171,271 *Record numbers including AC=0 |
| Japanese Genotype-phenotype Archive Dataset ID | JGAD000777 |
| Total Data Volume | 41.6 TB (fastq, vcf) |
| Comments (Policies) | NBDC policy |
| Participants/Materials | 256 gastric cancer (ICD10: C16) patients registered in BBJ 1st cohort |
| Targets | WGS |
| Target Loci for Capture Methods | - |
| Platform | Illumina [HiSeq 2500] |
| Library Source | DNA extracted from peripheral blood cells |
| Cell Lines | - |
| Library Construction (kit name) | TruSeq Nano DNA Library Preparation Kit |
| Fragmentation Methods | Ultrasonic fragmentation |
| Spot Type | Paired-end |
| Read Length (without Barcodes, Adaptors, Primers, and Linkers) | 2 x 125 bp |
| Japanese Genotype-phenotype Archive Dataset ID | JGAD000831 |
| Total Data Volume | 21.5 TB (fastq) |
| Comments (Policies) | NBDC policy |
| Participants/Materials | 269,000 patients (51 diseases) registered in BBJ 1st and 2nd cohort |
| Targets | SNP array |
| Target Loci for Capture Methods | - |
| Platform | Illumina [HumanHap550, Human610-Quad v1, HumanExome-12 v1, Infinium OmniExpress-24, Infinium HumanOmniExpressExome-8, Infinium HumanOmniExpressExome-8 v1.2, Infinium HumanOmniExpressExome-8 v1.3, Infinium HumanOmniExpressExome-8 v1.4, Infinium HumanOmniExpressExome-8 v1.6] |
| Library Source | DNA extracted from peripheral blood cells |
| Cell Lines | - |
| Reagents (Kit, Version) | HumanHap550 kit, Human610-Quad kit v1, HumanExome-12 kit v1, Infinium OmniExpress-24 kit, Infinium HumanOmniExpressExome-8 kit, Infinium HumanOmniExpressExome-8 kit v1.2, Infinium HumanOmniExpressExome-8 kit v1.3, Infinium HumanOmniExpressExome-8 kit v1.4, Infinium HumanOmniExpressExome-8 kit v1.6 |
| Genotype Call Methods (software) | - |
| Filtering Methods | - |
| Marker Numbers (after QC) | - |
| Japanese Genotype-phenotype Archive Dataset ID | JGAD000836 |
| Total Data Volume | 3.1 TB (idat) |
| Comments (Policies) | NBDC policy |
| Participants/Materials | 617 colorectal cancer (ICD10: C18, C19, C20) patients registered in BBJ 1st and 2nd cohort |
| Targets | WGS |
| Target Loci for Capture Methods | - |
| Platform | Illumina [HiSeq 2500] |
| Library Source | DNA extracted from peripheral blood cells |
| Cell Lines | - |
| Library Construction (kit name) | TruSeq Nano DNA Library Preparation Kit |
| Fragmentation Methods | Ultrasonic fragmentation |
| Spot Type | Paired-end |
| Read Length (without Barcodes, Adaptors, Primers, and Linkers) | 2 x 125 bp |
| Japanese Genotype-phenotype Archive Dataset ID | JGAD000832 |
| Total Data Volume | 25.5 TB (fastq) |
| Comments (Policies) | NBDC policy |
| Participants/Materials |
2,162 diabetes (ICD10: E11) patients registered in BBJ 1st cohort 2,067 gastric cancer (ICD10: C16) patients registered in BBJ 1st cohort |
| Targets | WGS |
| Target Loci for Capture Methods | - |
| Platform | Illumina [HiSeq 2500] |
| Library Source | DNA extracted from peripheral blood cells |
| Cell Lines | - |
| Library Construction (kit name) | TruSeq Nano DNA Library Preparation Kit |
| Fragmentation Methods | Ultrasonic fragmentation |
| Spot Type | Paired-end |
| Read Length (without Barcodes, Adaptors, Primers, and Linkers) | 2 x 125 bp |
| Japanese Genotype-phenotype Archive Dataset ID | |
| Total Data Volume |
JGAD000833: 20.0 TB (fastq) JGAD000834: 18.7 TB (fastq) |
| Comments (Policies) | NBDC policy |
TogoImputation reference panel (JGAD000867 /JGAD000868)
| Participants/Materials |
[JGAD000867] - WGS data (JGAD000220) of the biobank Japan project (N=1,026) [JGAD000868] - WGS data (JGAD000495) of the biobank Japan project (N=1,964) |
| Targets |
a reference panel from WGS data (variants on autosomal chromosomes and X-chromosome) |
| Target Loci for Capture Methods | - |
| QC |
Germline whole genome sequencing data were processed, and the aggregate VCF was calculated. Variants were then filtered based on the following conditions: (1) Variants that did not pass the VQSR filter were excluded (2) Multi-allelic sites were excluded (3) Variants with a call rate below 95% were excluded (4) Variants deviating from Hardy-Weinberg equilibrium (P < 1e-10) were excluded (5) Variants with a minor allele count (MAC) less than 2 were excluded
|
| Deduplication | GATK MarkDuplicates (version 4.1.0.0) |
| Calibration for re-alignment and base quality | - |
| Mapping Methods | bwa mem (version 0.7.15) |
| Mapping Quality | - |
| Reference Genome Sequence | GRCh38 |
| Coverage (Depth)
|
Mean ± Standard deviation JGAD000867: 28.70 ± 4.16 JGAD000868: 19.61 ± 5.41 |
| Detecting Methods for Variation |
GATK HaplotypeCaller -ERC GVCF (version 4.1.0.0) The ploidy for variant call was set as follows: Autosomes and pseudoautosomal regions (PARs): ploidy=2 Non-PARs on the X chromosome: ploidy=2 (female) and ploidy=1 (male) Non-PARs on the Y chromosome: ploidy=1 (male) |
| Method for phasing vcf files | After quality control, phasing was performed using Beagle program version 5.2 (21Apr21.304). |
| Variant Numbers in reference panel |
JGAD000867: 17,167,510 variants (autosomal chromosomes: 16,677,000 variants, X-chromosome: 490,510 variants) JGAD000868: 21,596,248 variants (autosomal chromosomes: 21,157,732 variants, X-chromosome: 438,516 variants) |
| Japanese Genotype-phenotype Archive Dataset ID | |
| Dataset ID of the Processed data by JGA | |
| Total Data Volume |
JGAD000867: 3.3 GB (vcf.gz) JGAD000868: 6.2 GB (vcf.gz) |
| Comments (Policies) | NBDC policy |
DATA PROVIDER
Principal Investigator: Michiaki Kubo
Affiliation: RIKEN Center for Integrative Medical Sciences
Project / Group Name: Tailor-made Medical Treatment Program (Bio Bank Japan: BBJ)
URL: https://biobankjp.org/english/index.html
Funds / Grants (Research Project Number) :
| Name | Title | Project Number |
|---|---|---|
| Ministry of Education, Culture, Sports, Science and Technology in Japan | Tailor-made Medical Treatment Program (the 3rd phase) | - |
| Tailor-Made Medical Treatment with the BioBank Japan Project (BBJ), Japan Agency for Medical Research and Development (AMED) | Generating large-scale data of genetic polymorphism to identify disease-related genes | 17km0305002h0005 |
| Project for Cancer Research and Therapeutic Evolution (P-CREATE), Japan Agency for Medical Research and Development (AMED) | Exploration of special and temporal diversity in genome and epigenome of hematological malignancies based on large-scale sequencing analyses. | JP19cm0106501 |
| Core Research and Evolutional Science and Technology, Advanced Research & Development Programs for Medical Innovation, Japan Agency for Medical Research and Development (AMED-CREST) | Research on altered tissue functions caused by clonal expansion and remodeling of apparently normal tissues related to normal aging or exposure to chronic inflammation and other lifestyles | JP19gm1110011 |
| KAKENHI Grant-in-Aid for Scientific Research (S) | Comprehensive studies on the molecular basis of early development and clonal evolution in cancer using advanced genomics. | 19H05656 |
| Program for Promoting Platform of Genomics based Drug Discovery, Project for Genome and Health Related Data, Japan Agency for Medical Research and Development (AMED) | Development of a large-scale database for effective drug treatment for breast, colorectal, and pancreas cancers | JP19kk0305010 |
| KAKENHI Grant-in-Aid for Early-Career Scientists | Genome-wide association study integrating mobile genetic elements | 22K15385 |
| KAKENHI Grant-in-Aid for Scientific Research (B) | Elucidation of genetic factors that define myocardial vulnerability as a basis for the development of heart failure | 21H02919 |
| KAKENHI Grant-in-Aid for Scientific Research (S) | Genome immunity: elucidation of the antiviral activity of endogenous bornaviruses and their utilization as functional resources | 20H05682 |
| KAKENHI Grant-in-Aid for Scientific Research (B) | Integration and reactivation of human herpesvirus 6: association with diseases | 21H02972 |
| Biobank - Construction and Utilization biobank for genomic medicine REalization (B-Cure), Japan Agency for Medical Research and Development (AMED) | Management of the Japanese biobank | JP19km0605001 |
| Practical Research Project for Life-Style related Diseases including Cardiovascular Diseases and Diabetes Mellitus, Japan Agency for Medical Research and Development (AMED) | Multi-layered and integrated research for prevention of atrial fibrillation and serious complications | JP22ek0210164 |
| Biobank - Construction and Utilization biobank for genomic medicine REalization, Japan Agency for Medical Research and Development (AMED) | Understanding pathogenesis of atrial fibrillation and implementation of precision medicine by WGS and multi-omics | JP21tm0724601 |
| Biobank - Construction and Utilization biobank for genomic medicine REalization, Japan Agency for Medical Research and Development (AMED) | Implementation of next-generation precision medicine for cardiovascular disease by multi-omics | JP20km0405209 |
| Practical Research Project for Rare / Intractable Diseases, Japan Agency for Medical Research and Development (AMED) | Understanding pathology and implementation of precision medicine for intractable cardiovascular disease by multi-omics analysis | JP20ek0109487 |
PUBLICATIONS
| Title | DOI | Dataset ID | |
|---|---|---|---|
| 1 | A genome-wide association study identifies PLCL2 and AP3D1-DOT1L-SF3A2 as new susceptibility loci for myocardial infarction in Japanese. | doi:10.1038/ejhg.2014.110 | hum0014.v1.freq.v1 |
| 2 | A functional variant in ZNF512B is associated with susceptibility to amyotrophic lateral sclerosis in Japanese. | doi:10.1093/hmg/ddr268 | hum0014.v2.jsnp.92als.v1 |
| 3 | Functional variants in ADH1B and ALDH2 coupled with alcohol and smoking synergistically enhance esophageal cancer risk. | doi: 10.1053/j.gastro.2009.07.070 | hum0014.v2.jsnp.182ec.v1 |
| 4 | SNPs in KCNQ1 are associated with susceptibility to type 2 diabetes in East Asian and European populations. | doi: 10.1038/ng.208 | T2DM (JSNP) |
| 5 | Common variants in a novel gene, FONG on chromosome 2q33.1 confer risk of osteoporosis in Japanese. | doi: 10.1371/journal.pone.0019641 | Osteoporosis (JSNP) |
| 6 | Genome-wide association studies in the Japanese population identify seven novel loci for type 2 diabetes. | doi: 10.1038/ncomms10531 | |
| 7 | Multi-ancestry genome-wide association study of 21,000 cases and 95,000 controls identifies new risk loci for atopic dermatitis. | doi: 10.1038/ng.3424 | hum0014.v4.AD.v1 |
| 8 | Genome-wide association study identifies eight new susceptibility loci for atopic dermatitis in the Japanese population. | doi: 10.1038/ng.2438 | hum0014.v4.AD.v1 |
| 9 | Identification of six new genetic loci associated with atrial fibrillation in the Japanese population. | doi: 10.1038/ng.3842 | hum0014.v5.AF.v1 |
| 10 | Genome-wide association study identifies 112 new loci for body mass index in the Japanese population. | doi:10.1038/ng.3951 | |
| 11 | Genome-wide association study identifies seven novel susceptibility loci for primary open-angle glaucoma. | doi: 10.1093/hmg/ddy053 | hum0014.v7.POAG.v1 |
| 12 | Genetic analysis of quantitative traits in the Japanese population links cell types to complex human diseases. | doi:10.1038/s41588-018-0047-6 | |
| 13 | Elucidating the genetic architecture of reproductive ageing in the Japanese population | doi: 10.1038/s41467-018-04398-z | |
| 14 | Deep whole-genome sequencing reveals recent selection signatures linked to evolution and disease risk of Japanese. | doi: 10.1038/s41467-018-03274-0 | JGAD000220 |
| 15 | Germline pathogenic variants of 11 breast cancer genes in 7,051 Japanese patients and 11,241 controls. | doi: 10.1038/s41467-018-06581-8 | JGAD000209 |
| 16 | A Variant within the FTO confers susceptibility to diabetic nephropathy in Japanese patients with type 2 diabetes | doi: 10.1371/journal.pone.0208654 | hum0014.v12.T2DMwN.v1 |
| 17 | Identification of 28 new susceptibility loci for type 2 diabetes in the Japanese population | doi: 10.1038/s41588-018-0332-4 | hum0014.v13.T2DMmeta.v1 |
| 18 | GWAS of smoking behaviour in 165,436 Japanese people reveals seven new loci and shared genetic architecture. | doi: 10.1038/s41562-019-0557-y | |
| 19 | Characterizing rare and low-frequency height-asssociated variants in the Japanese population | doi: 10.1038/s41467-019-12276-5 | |
| 20 | Germline pathogenic variants in 7,636 Japanese patients with prostate cancer and 12,366 controls. | doi: 10.1093/jnci/djz124 | JGAD000288 |
| 21 | Large-scale genome-wide association study in a Japanese population identifies novel susceptibility loci across different diseases | doi: 10.1038/s41588-020-0640-3 | |
| 22 | GWAS of 165,084 Japanese individuals identified nine loci associated with dietary habits | doi: 10.1038/s41562-019-0805-1 | hum0014.v19 |
| 23 | Population-specific and transethnic genome-wide analyses identify distinct and shared genetic risk loci for coronary artery disease. | doi: 10.1038/s41588-020-0705-3 | hum0014.v20.cad.v1 |
| 24 | Genetic characterization of pancreatic cancer patients and prediction of carrier status of germline pathogenic variants in cancer-predisposing genes | doi: 10.1016/j.ebiom.2020.103033 | JGAD000438 |
| 25 | Population-based Screening for Hereditary Colorectal Cancer Variants in Japan | doi: 10.1016/j.cgh.2020.12.007 | |
| 26 | Genome-wide association study reveals BET1L associated with survival time in the 137,693 Japanese individuals | doi: 10.1038/s42003-023-04491-0 | hum0014.v27.surv.v1 |
| 27 | Cross-ancestry genome-wide analysis of atrial fibrillation unveils disease biology and enables cardioembolic risk prediction | doi: 10.1038/s41588-022-01284-9 | hum0014.v29.AF.v1 |
| 28 | Association between germline pathogenic variants in cancer-predisposing genes and lymphoma risk | doi: 10.1111/cas.15522 | |
| 29 | Helicobacter pylori, Homologous-Recombination Genes, and Gastric Cancer | doi: 10.1056/NEJMoa2211807 | |
| 30 | Germ line DDX41 mutations define a unique subtype of myeloid neoplasms | doi: 10.1182/blood.2022018221 | |
| 31 | Combined landscape of single-nucleotide variants and copy number alterations in clonal hematopoiesis | doi: 10.1038/s41591-021-01411-9 | |
| 32 | Characterizing rare and low-frequency height-associated variants in the Japanese population | doi: 10.1038/s41467-019-12276-5 | JGAD000777 |
| 33 | Chromosomal alterations among age-related haematopoietic clones in Japan | doi: 10.1038/s41586-020-2426-2 | |
| 34 | Detection of trait-associated structural variations using short-read sequencing | doi: 10.1016/j.xgen.2023.100328 | JGAD000831 |
USRES (Controlled-access Data)
| Principal Investigator | Affiliation | Country/Region | Research Title | Data in Use (Dataset ID) | Period of Data Use |
|---|---|---|---|---|---|
| Mark Daly | Broad Institute of MIT and Harvard | JGAD000101, JGAD000102, JGAD000123, JGAD000124, JGAD000144-JGAD000201, JGAD000220 |
2018/09/11-2023/07/31 | ||
| Yukinori Okada | Department of Statistical Genetics, Osaka University Graduate School of Medicine | JGAD000101, JGAD000102, JGAD000123, JGAD000124, JGAD000144-JGAD000201, JGAD000220 |
2018/09/20-2021/03/31 | ||
| Shigeo Kamitsuji | Statistical Analysis Division, StaGen Co., Ltd. | JGAD000123 | 2018/10/04-2019/03/31 | ||
| Katsushi Tokunaga | Department of Human Genetics, Graduate School of Medicine, The University of Tokyo | JGAD000123, JGAD000124, JGAD000144-JGAD000201, JGAD000220 |
2018/11/13-2026/11/08 | ||
| Tatsuhiko Tsunoda | Department of Medical Science Mathematics, Medical Research Institute, Tokyo Medical and Dental University | Research on big data analysis for precision medicine | JGAD000123, JGAD000124, JGAD000144-JGAD000201, JGAD000220 |
2018/12/18-2021/06/19 | |
| Liming Liang | Harvard T.H. Chan School of Public Health, Department of Epidemiology | JGAD000123 | 2019/01/21-2021/12/31 | ||
| Masao Nagasaki | Center for Genomic Medicine, Graduate School of Medicine Center for the Promotion of Interdisciplinary Education and Research, Kyoto University | Development and application of bioinformatics methods to facilitate the detection of genes associated with multifactorial disorders based on large-scale whole genome sequencing data of Japanese individuals | JGAD000123, JGAD000124, JGAD000144-JGAD000201, JGAD000220 |
2019/01/31-2027/03/31 | |
| Seishi Ogawa | Department of Pathology and Tumor Biology, Graduate School of Medicine, Kyoto University | JGAD000209 | 2019/02/04-2021/03/31 | ||
| Shigeo Kamitsuji | Statistical Analysis Division, StaGen Co., Ltd. | JGAD000123 | 2019/03/13-2022/03/31 | ||
| Takashi Kohno | National Cancer Research Institute, Division of genome biology | JGAD000123, JGAD000124, JGAD000220 |
2019/04/15-2019/12/31 | ||
| Shigeo Horie | Department of Urology, Juntendo University, Graduate School of Medicine | JGAD000123, JGAD000220 | 2019/05/14-2024/03/31 | ||
| Tatsuhiko Tsunoda | Department of Medical Science Mathematics, Medical Research Institute, Tokyo Medical and Dental University | Research on sequence, image data analysis for precision medicine | JGAD000123, JGAD000124, JGAD000144-JGAD000201, JGAD000220 |
2019/06/06-2023/08/31 | |
| Kengo Kinoshita | Tohoku Medical Megabank Organization | Construction of Japanese whole genome database | JGAD000220 | 2019/06/24-2022/03/31 | |
| Kouya Shiraishi | Division of Genome Biology, National Cancer Research Institute | Elucidation of immune-system networks between host and tumor based on genomic analysis | JGAD000124 | 2019/08/05-2023/03/31 | |
| Shigeo Kamitsuji | Statistical Analysis Division, StaGen Co., Ltd. | Mendelian randomization study using genetic markers of uric acid levels as an instrumental variable | JGAD000123, JGAD000124, JGAD000146, JGAD000148, JGAD000149, JGAD000155, JGAD000156, JGAD000157, JGAD000174, JGAD000188 |
2019/08/16-2024/03/31 | |
| Shigeo Kamitsuji | Statistical Analysis Division, StaGen Co., Ltd. | Mendelian randomization study using 58 clinical laboratory tests and SNP genotype data. | JGAD000123, JGAD000124, JGAD000144-JGAD000201 |
2019/08/22-2024/03/31 | |
| Osamu Ogasawara | Bioinformation and DDBJ Center, National Institute of Genetics | Evaluation of human genome analysis workflow using JGA/AGD genome data. | JGAD000123, JGAD000220 | 2019/10/11-2024/03/31 | |
| Seishi Ogawa | Department of Medical Science, Kyoto University | Comprehensive analysis of genetic alterations in hematological malignancies | JGAD000102, JGAS000123, JGAD000220 |
2019/11/14-2024/03/31 | |
| Yasushi Okazaki | Diagnostics and Therapeutics of Intractable Diseases, Juntendo University Graduate School of Medicine | Identification of disease biomarkers by disease cohort research network -Whole genome sequencing of epilepsy- | JGAD000123 | 2020/06/04-2023/03/31 | |
| Chihiro Hata | Bioinformation and DDBJ Center, National Institute of Genetics | Identification of hypomorphic mutations in Japanese breast cancer patients | JGAD000209 | 2020/06/04-2023/03/31 | |
| Yosuke Kawai | Genome Medical Science Project, National Center for Global Health and Medicine | Large scale genome analysis of modern human genomes to infer the origin of Yaponesians | JGAD000123, JGAD000124, JGAD000144-JGAD000201, JGAD000220 |
2020/06/19-2022/03/31 | |
| Nakao Iwata | Department of Psychiatry, Fujita Health University School of Medicine | Research for investigating susceptibility of mental state, mental disorders, drug efficacy and side effects through genetic analysis | JGAD000123, JGAD000124 | 2020/08/17-2022/12/31 | |
| Atray Dixit | Coral Genomics, Inc. | Derivation and Evaluation of Functional Response Scores | JGAD000101, JGAD000123, JGAD000124, JGAD000144-JGAD000201, JGAD000220 |
2020/08/24-2021/07/21 | |
| Hae Kyung Im | Biological Sciences Division, University of Chicago | Predicted Gene Expression: High Power, Mechanism, and Direction of Effect | JGAD000123, JGAD000124, JGAD000144-JGAD000201, JGAD000220 |
2020/09/15-2023/06/23 | |
| Hongyu Zhao | Department of Biostatistics, Yale School of Public Health | Leveraging multi-ethnic data and functional annotations in causal variant identification, genetic correlation estimation, and genetic risk prediction | JGAD000101, JGAD000102, JGAD000123, JGAD000124, JGAD000144-JGAD000201, JGAD000220 |
2020/09/24-2024/03/01 | |
| Charleston Chiang | Center for Genetic Epidemiology, Keck School of Medicine, University of Southern Califolnia | Investigating the evolution of complex genetic architecture in participants of Biobank Japan | JGAD000101, JGAD000102, JGAD000123, JGAD000124, JGAD000144-JGAD000201, JGAD000220 |
2020/09/28-2025/07/01 | |
| Shigeo Kamitsuji | Statistical Analysis Division, StaGen Co., Ltd. | Identifying the genetic risk factors for Stent Thrombosis by genome-wide association study | JGAD000123, JGAD000124, JGAD000145, JGAD000146, JGAD000149, JGAD000151, JGAD000155, JGAD000156, JGAD000158, JGAD000159, JGAD000163, JGAD000165-JGAD000167, JGAD000170, JGAD000172-JGAD000175, JGAD000182, JGAD000187-JGAD000189, JGAD000192-JGAD000196, JGAD000200, JGAD000201 |
2020/10/26-2025/03/31 | |
| Ali Torkamani | Scripps Research Institute | Genomics Deep Learning | JGAD000101, JGAD000102, JGAD000123, JGAD000124, JGAD000144-JGAD000201, JGAD000220 |
2020/11/16-2023/07/10 | |
| Kazuhiro Nakayama | Department of Integrated Biosciences, Graduate School of Frontier Sciences, The University of Tokyo | Investigation of genome variation influening activity of brown adipose tissues | JGAD000123, JGAD000124 | 2020/11/26-2023/09/18 | |
| Keishi Fujio | Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo | Integrative analysis of immune-cell eQTL data and large-scaled GWAS data in Japanese | JGAD000101, JGAD000102, JGAD000123, JGAD000124, JGAD000144-JGAD000201, JGAD000220 |
2020/12/14-2025/03/31 | |
| Masataka Kikuchi | Department of Computational Biology and Medical Sciences, Graduate School of Frontier Science, The University of Tokyo | Japan | Imputation analysis using a Japanese reference panel | JGAD000220 | 2020/12/14-2027/06/30 |
| Fumihiko Matsuda | Center for Genomic Medicine, Kyoto University | Elucidation of Japanese genetic diversity | JGAD000220 | 2021/01/05-2025/03/31 | |
| Emiko Noguchi | Department of Medical Genetics, Faculty of Medicine, University of Tsukuba | Exploratory study of genetic factors in allergic diseases | JGAD000220 | 2021/03/16-2032/03/31 | |
| Noriko Sato | Department of Molecular Epidemiology, Medical Research Institute, Tokyo Medical and Dental University | Analysis of genetic and environmental risks of obesity and diabetes based on regional cohort longitudinal data | JGAD000220 | 2021/04/09-2023/03/31 | |
| Takashi Kohno | Division of Genome Biology, National Cancer Center Research Institute | Identification of genetic risk factors in AYA(Adolescence and Young Adult) cancer | JGAD000209, JGAD000220 | 2021/05/20-2025/03/31 | |
| Yasunobu Nagata | Department of hematology, Nippon Medical School | Identification of the mechanisms for pathogenesis of hematologic tumors based on novel genetic abnormalities | JGAD000123, JGAD000124, JGAD000144-JGAD000201, JGAD000220 |
2021/05/26-2026/03/31 | |
| Atsushi Kawakami | Department of Immunology and Rheumatology, Nagasaki University Hospital | An exploratory study to determine the genetic polymorphisms or mutations associated with type 1 diabetes and interstitial lung disease induced by immune checkpoint inhibitor; nivolumab | JGAD000220 | 2021/06/14-2022/03/30 | |
| Akihiro Fujimoto | Department of Human Genetics, Graduate School of Medicine, The University of Tokyo | Comprehensive analysis of mutations and genetic diversity by analyzing whole-genome sequence data | JGAD000220, JGAD000410 | 2021/09/16-2024/11/30 | |
| Yoshihiro Asano | Department of Cardiovascular Medicine Graduate School of Medicine, Osaka University | Sensitive gene analysis of hereditary cardiovascular disease | JGAD000123, JGAD000124, JGAD000144-JGAD000201, JGAD000220 | 2021/07/16-2022/05/31 | |
| Hironori Masuko | Department of Pulmonary Medicine, University of Tsukuba | Search for susceptibility genes for chronic inflammatory airway diseases | JGAD000123 | 2021/08/11-2023/03/31 | |
| Takashi Kohno | Division of Genome Biology, National Cancer Center Research Institute | Identification of genetic risk factors in AYA(Adolescence and Young Adult) cancer | JGAD000209, JGAD000220 | 2021/09/27-2025/03/31 | |
| Fumihiko Matsuda | Center for Genomic Medicine, Kyoto University | Development of personalized medicine | JGAD000123, JGAD000220 | 2021/09/27-2025/03/31 | |
| Takashi Matsuda | Advanced Informatics & Analytics, Astellas Pharma Inc. | Investigation of the correlation between Liver cancer/Hepatitis B and polymorphism | JGAD000102, JGAD000123 | 2021/11/05-2022/07/31 | |
| Emiko Noguchi | Department of Medical Genetics, Faculty of Medicine, University of Tsukuba | Identification of the pathogenic factors for food allergy | JGAD000220 | 2021/12/03-2025/03/31 | |
| Yosuke Kawai | Division of Molecular Pathology, The Institute of Medical Science, The University of Tokyo | Population Genetic Analysis of the Origin of Japanese Populations | JGAD000123 | 2021/12/08-2023/03/31 | |
| Toshiharu Ninomiya | Department of Epidemiology and Public Health, Graduate School of Medical Sciences, Kyushu University | Japan Prospective Studies Collaboration for Aging and Dementia (JPSC-AD) | JGAD000220 | 2021/12/08-2026/2/28 | |
| Joshua Chiou | Internal Medicine Research Unit, Pfizer | Evaluating GWAS associations from Biobank Japan to Support Confidence in Rationale for Therapeutic Targets | JGAD000123, JGAD000124, JGAD000144-JGAD000201, JGAD000220 | 2022/01/27-2022/12/31 | |
| Gil McVean | Genomics plc | United Kingdom of Great Britain and Northern Ireland | Development of polygenic risk scores in diverse ancestries for diseases, traits and conditions | JGAD000101, JGAD000102 | 2022/07/19-2025/07/01 |
| Gil McVean | Genomics plc | United Kingdom of Great Britain and Northern Ireland | Using large-scale reference panels for imputation and ancestry analysis to support target discovery and polygenic risk score models | JGAD000220, JGAD000410 | 2022/08/04-2025/08/01 |
| Hirofumi Nakaoka | Department of Cancer Genome Research, Sasaki Institute | Japan | Analysis of hypomorphic variants in breast cancer-associated genes by using large-scale sequencing data sets | JGAD000209 | 2022/08/17-2024/03/31 |
| Emiko Noguchi | Department of Medical Genetics, Faculty of Medicine, University of Tsukuba | Japan | Research on genetic predisposition to inflammatory lung disease | JGAD000220 | 2022/09/19-2027/03/31 |
| Nuria Lopez-Bigas | Institute for Research in Biomedicine (IRB Barcelona) | Spain | Study of the genetic basis of clonal hematopoiesis | JGAD000399, JGAD000400 | 2022/11/06-2025/08/01 |
| Keiko Yamazaki | Department of Public Health, Graduate School of Medicine, Chiba University | Japan | Prediction of effectiveness to molecular target drugs in Japanese patients with inflammatory bowel disease | JGAD000220 | 2022/11/09-2025/03/31 |
| Ryosuke Kitoh | Department of Otorhinolaryngology-Head and Neck Surgery, Shinshu University School of Medicine | Japan | Genome-wide association study of the sudden sensorineural hearing loss | JGAD000123 | 2022/12/19-2027/03/31 |
| Shigeo Kamitsuji | Statistical Analysis Division, StaGen Co., Ltd. | Japan | Genome-Wide Association Study to identify genetic factors for strabismus in Japanese population | JGAD000123 | 2023/02/13-2027/02/28 |
| Kei Yura | Graduate School of Humanities and Sciences, Ochanomizu University | Japan | Phenotype Prediction of Cancer Suppressor Gene BRCA1 variants | JGAD000220 | 2023/03/16-2025/03/31 |
| Yoshihiro Onouchi | Department of Public Health, Graduate School of Medicine, Chiba University | Japan | A Multicenter Study to Identify Genetic Factors in Kawasaki Disease | JGAD000220 | 2023/03/30-2025/03/31 |
| Yoshihiro Onouchi | Department of Public Health, Graduate School of Medicine, Chiba University | Japan | A study of the genetic background of differences in antibody response to COVID-19 vaccine | JGAD000220 | 2023/04/19-2025/12/31 |
| Masaki Kato | kansai medical university | Japan | Exploratory and validation study of genetic and biological factors for the development of precision medicine algorithms for psychiatric disorders | JGAD000101, JGAD000102, JGAD000123, JGAD000220 |
2023/08/25-2028/06/30 |
| Hiroki Kimura | Department of Psychiatry, Nagoya University Graduate school of medicine | Japan | Research on elucidation of susceptibility to brain and mental illness (vulnerability to disease onset) and efficacy and side effects of drugs (treatment responsiveness) through genetic analysis | JGAD000220 | 2023/11/17-2025/10/28 |
| Chikashi Terao | Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences | Japan | Research on personalized medicine based on genomics information | JGAD000123, JGAD000124, JGAD000144-JGAD000201, JGAD000220 |
2023/11/21-2026/03/31 |
| Yasuhiro Mochida | Kidney Disease and Transplant center, Shonan Kamakura General Hospital | Japan | Association between Clonal hematopoiesis of indeterminate potential and Chronic Kidney Disease in Japanese cohort study | JGAD000399, JGAD000400 | 2024/02/07-2027/03/31 |
| Hiroyuki Mishima | Department of Human Genetics, Atomic Bomb Disease Institute, Nagasaki University | Japan | Development of Methods to Mitigate Batch Effects in Human Whole Genome Sequencing | JGAD000220 | 2024/04/17-2027/03/31 |
| Chikashi Terao | Clinical Research Center, Shizuoka General Hospital | Japan | Investigation of Genetic Factors Associated with Human Phenotypic Traits | JGAD000220, JGAD000495, JGAD000777 |
2024/04/17-2028/12/03 |
| Koichi Matsuda | Department of Computational Biology and Medical Sciences, Graduate school of Frontier Sciences, The University of Tokyo | Japan | Disease Cohort Research Network for Disease Marker Exploratory Studies | JGAD000209, JGAD000220, JGAD000288, JGAD000438, JGAD000458-JGAD000460, JGAD000495, JGAD000531, JGAD000720, JGAD000721, JGAD000777, JGAD000831-JGAD000834 |
2024/06/17-2029/03/31 |
| Masao Nagasaki | Division of Biomedical Information Analysis, Medical Research Center for High Depth Omics, Medical Institute of Bioregulation, Kyushu University | Japan | Development and application of bioinformatics methods to facilitate the detection of genes associated with multifactorial disorders based on large-scale whole genome sequencing data of Japanese individuals | JGAD000123, JGAD000124, JGAD000144-JGAD000201, JGAD000220 |
2024/06/24-2027/03/31 |
| Kouya Shiraishi | Department of Clinical Genomics, National Cancer Center Research Institute | Japan | Search for genes involved in susceptibility to lung cancer | JGAD000123 | 2024/06/24-2025/12/31 |
| Chikashi Terao | Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences | Japan | Research on personalized medicine based on genomics information | JGAD000836 | 2024/07/08-2026/03/31 |
| Chikashi Terao | Clinical Research Center, Shizuoka General Hospital | Japan | Investigation of Genetic Factors Associated with Human Phenotypic Traits | JGAD000836 | 2024/07/16-2028/12/03 |
| Taisei Mushiroda | Laboratory for Pharmacogenomics, RIKEN Center for Integrative Medical Sciences | Japan | Search of genomic biomarkers associated with drug-induced eruptions | JGAD000220 | 2024/08/01-2028/03/31 |
| Masahiro Nakatochi | Public Health Informatics, Department of Integrated Sciences, Nagoya University Graduate School of Medicine | Japan | Exploration of genetic factors involved in the onset, progression, and prognosis of amyotrophic lateral sclerosis | JGAD000679 | 2024/08/27-2030/03/31 |
hum0014.v34_release note
hum0014 Release Note
| Research ID | Release Date | Type of Data |
|---|---|---|
| hum0014.v34 | 2024/09/19 |
Processed data of JGAD000220 (WGS for 1,026 individuals) by JGA (data for the use of TogoImputation) Processed data of JGAD000495 (WGS for 1,964 individuals) by JGA (data for the use of TogoImputation) |
| hum0014.v33 | 2024/05/27 |
WGS for 256 gastric cancer patients SNP array for 269,000 patients (51 diseases) in BBJ 1st and 2nd cohort WGS for 617 colorectal cancer patients WGS for 2,162 diabetes patients WGS for 2,067 gastric cancer patients |
| hum0014.v32 | 2024/01/11 | WGS for 1,007 individuals |
| hum0014.v31 | 2023/09/01 |
Processed data of JGAD000220 (WGS for 1,026 individuals) by JGA (CRAM, gVCF) Processed data (joint call) of JGAD000220 (WGS for 1,026 individuals) by JGA (aggregate VCF) Processed data of JGAD000220 (reference panel) by JGA (data for the use of TogoImputation) |
| hum0014.v30 | 2023/04/20 | target sequencings of 27 cancer-predisposing genes in 1,982 lymphoma patients, 10,366 gastric cancer patients and 37,592 controls |
| hum0014.v29 | 2023/04/05 |
GWAS for 9,826 AF patients and 140,446 controls from BBJ 1st cohort GWAS meta-analysis for 77,690 AF patients and 1,167,040 controls |
| hum0014.v28 | 2023/04/05 | mobile element variations in 4,880 individuals from the BBJ 1st cohort |
| hum0014.v27 | 2022/12/31 | GWAS for survival time in 137,693 individuals from the BBJ 1st cohort |
| hum0014.v26 | 2022/04/01 | target sequencings of 27 cancer-predisposing genes and 13 renal cell carcinoma-related genes in 740 renal cell cancer patients and 5,996 controls |
| hum0014.v25 | 2022/01/25 | WGS for 1,765 myocardial infarction patients and 199 dementia patients |
| hum0014.v24 | 2021/11/26 | target sequencing of 27 cancer-predisposing genes in 1,005 pancreatic cancer patients, 12,503 colorectal cancer patients and 23,705 controls |
| hum0014.v23 | 2021/07/13 | bam/gvcf data of WGS (JGAD000220) |
| hum0014.v22 | 2021/05/21 | targeted sequencing of 23 genes related to clonal hematopoiesis and SNP-array in 11,234 subjects extracted from approximately 200,000 subjects registered in Biobank Japan between fiscal years 2003 to 2007 |
| hum0014.v21 | 2020/08/25 | GWAS for coronary artery disease |
| hum0014.v20 | 2020/08/17 | GWAS for coronary artery disease |
| hum0014.v19 | 2020/04/20 | GWAS for dietary habits |
| hum0014.v18 | 2019/11/26 | GWAS for Breast cancer |
| hum0014.v17 | 2019/10/08 | GWAS for 40 diseases |
| hum0014.v16 | 2019/10/07 | target sequencing of 8 hereditary prostate cancer genes in 7,636 prostate cancer patients and 12,366 controls |
| hum0014.v15 | 2019/09/27 |
reference panel by using of WGS data of the biobank Japan project (N=1,037) and 1KGP p3v5 ALL (N=2,504) GWAS for height |
| hum0014.v14 | 2019/03/26 | GWAS for smoking behavior |
| hum0014.v13 | 2019/01/25 | meta analysis of 4 GWASs for T2DM |
| hum0014.v12 | 2018/12/10 | meta analysis of 2 GWASs for T2DM with diabetic nephropathy |
| hum0014.v11 | 2018/10/16 | target sequencing of 11 hereditary breast cancer genes in 7,104 breast cancer patients and 23,731 controls |
| hum0014.v10 | 2018/08/13 | WGS for 1,026 individuals |
| hum0014.v9 | 2018/08/07 | GWAS for age at menarche and menopause |
| hum0014.v8 | 2018/05/01 | GWAS for 58 quantitative traits |
| hum0014.v7 | 2018/04/04 | GWAS for POAG |
| hum0014.v6 | 2017/09/08 |
GWAS for BMI Genotype data for 182,505 individuals |
| hum0014.v5 | 2017/05/18 |
GWAS for AF Genotype data for 8180 AFs |
| hum0014.v4 | 2016/02/02 | GWAS for AD |
| hum0014.v3 | 2016/01/28 | GWASs for T2DM |
| hum0014.v2 | 2015/12/28 | Genotype frequencies of 934 healthy individuals, about 190 patients from each of 35 diseases, 182 esophageal cancer patients, and 92 ALS patients. |
| hum0014.v1 | 2014/09/30 | GWAS for MI |
hum0014.v34
The vcf (phased) files, tbi index files, the bref3 files, and a config file processed JGAD000220 (whole genome sequencing data for a total of 1,026 patients) and JGAD000495 (whole genome sequencing data for a total of 1,964 patients) in a certain workflow were provided. These files can be used in the TogoImputation. If you plan to use the data, please indicate both original data (JGAD000220 and JGAD000495) and processed data (JGAD000867 and JGAD000868) on the application form for data use.
hum0014.v33
Whole genome sequencing analysis for 256 gastric cancer patients registered in BBJ 1st cohort was performed. Fastq files are provided.
SNP array analysis for 269,000 patients (51 diseases) registered in BBJ 1st and 2nd cohort was performed. IDAT files are provided.
Whole genome sequencing analysis for 617 colorectal cancer patients registered in BBJ 1st and 2nd cohort was performed. Fastq files are provided.
Whole genome sequencing analysis for 2,162 diabetes patients registered in BBJ 1st cohort was performed. Fastq files are provided.
Whole genome sequencing analysis for 2,067 gastric cancer patients registered in BBJ 1st cohort was performed. Fastq files are provided.
hum0014.v32
Whole genome sequencing analysis for a total of 1,007 patients, who were registered Bio Bank Japan from 2003 - 2007 was performed. Fastq and vcf files are provided.
hum0014.v31
The alignment results [CRAM], variant call results per sample [gVCF] processed JGAD000220 (whole genome sequencing data for a total of 1,026 patients, who were registered BioBank Japan from 2003 - 2007) in a certain workflow were provided. If you plan to use the data, please indicate both original data (JGAD000220) and processed data (JGAD000690) on the application form for data use.
The variant call results per dataset [aggregated VCF, tabix] processed JGAD000220 (whole genome sequencing data for a total of 1,026 patients, who were registered BioBank Japan from 2003 - 2007) in a certain workflow were provided. If you plan to use the data, please indicate both original data (JGAD000220) and processed data (JGAD000758) on the application form for data use.
The tbi index file, the bref3 file, and a config file processed JGAD000220 (JGAS000114 reference panel) in a certain workflow were provided. These files can be used in the TogoImputation. If you plan to use the data, please indicate both original data (JGAD000220) and processed data (JGAD000679) on the application form for data use.
hum0014.v30
Target capture sequencing analyses of 27 cancer-predisposing genes in 1,982 lymphoma patients, 10,366 gastric cancer patients and 37,592 controls were performed. Fastq files are provided.
hum0014.v29
GWAS summary statistics file for 9,826 AF cases and 140,446 controls from the BBJ 1st cohort was added (txt).
Summary statistics file of cross-ancestry meta-analysis for 77,690 AF cases and 1,167,040 controls and polygenic risk score file calculated from the meta-analysis were added (txt).
hum0014.v28
Files for mobile element variations in 4,880 individuals from the BBJ 1st cohort were added (txt).
hum0014.v27
GWAS analysis files for 137,693 individuals from the BBJ 1st cohort were added (txt).
Sex-stratified genome-wide association studies using a Cox proportional hazard model under the assumption of the additive genetic model were performed. Associations of genetic variants estimated by saddle point estimation using SPACox software were also evaluated.
hum0014.v26
Target capture sequencing analyses of 27 cancer-predisposing genes and 13 renal cell carcinoma-related genes in 740 renal cell cancer patients and 5,996 controls were performed. Fastq files are provided.
hum0014.v25
Whole genome sequencing analysis for 1,765 myocardial infarction patients and 199 dementia patients were performed. Whole genome sequencing analyzed data were mapped to the GRCh37 reference genome sequence, and variant detection was carried out using the GATK (Genome Analysis Toolkit) standards. This project is an initiative of the GEnome Medical alliance Japan (GEM Japan, GEM-J). Fastq files, Bam files and gvcf files were provided.
hum0014.v24
A target capture sequencing analysis of 27 cancer-predisposing genes in 1,005 pancreatic cancer patients, 12,503 colorectal cancer patients and 23,705 controls was performed. Fastq files are provided.
hum0014.v23
Whole genome sequencing analyzed data included in the JGAD000220 were mapped to the GRCh37 reference genome sequence, and variant detection was carried out using the GATK (Genome Analysis Toolkit) standards. Bam files and gvcf files were added. This project is an initiative of the GEnome Medical alliance Japan (GEM Japan, GEM-J).
hum0014.v22
Target capture sequencing of 23 genes related to clonal hematopoiesis and SNP-array in 11,234 subjects extracted from approximately 200,000 subjects registered in Biobank Japan between fiscal years 2003 to 2007 were performed. A list of somatic SNVs/indels detected by targeted sequencing (txt) and a table of somatic copy-number alterations detected by analysis of SNP-array data (csv) are provided.
hum0014.v21
GWAS analysis files for coronary artery disease patients were added.
hum0014.v20
A total of 25,892 patients with coronary artery disease and 142,336 controls were genotyped by using of Illumina HumanOminiExpress, HumanExome, or OmniExpressExome BeadChip. A genotype imputation was carried out using Minimac3 algorithm with the BBJ-CAD reference panel. Then, genome-wide association study was performed using plink2 for 20 million variants.
hum0014.v19
A total of 165,084 participants whose dietary habits status is available were genotyped by using of Illumina HumanOminiExpress BeadChip, HumanExome, or OmniExpressExome BeadChip. A genotype imputation was carried out using Minimac algorithm with the 1000 genomes Phase I v3 release as a reference. Then, a genome-wide association study (about 6,000,000 imputed SNVs) was performed (BOLT-LMM and ProbABEL program).
hum0014.v18
GWAS analysis files for breast cancer patients were added.
hum0014.v17
A total of 212,453 patients of 40 diseases were genotyped by using of HumanOmniExpress/HumanExome/OmniExpressExome BeadChip(Illumina). A genotype imputation was carried out using Minimac3 algorithm with the 1000 genomes Phase 3 v5 release as a reference. Then, genome-wide association studies (8,919,992 imputed SNVs) were performed (SAIGE v0.29.4.2).
hum0014.v16
A target capture sequencing analysis of 8 hereditary prostate cancer genes in 7,636 prostate cancer patients and 12,366 controls was performed. Fastq files are provided.
hum0014.v15
- A new reference panel was build with WGS data of the biobank Japan project (N=1,037) and the 1KGP p3v5 ALL (N=2,504) .
- A total of 159,095 individuals were genotyped by using of Illumina HumanOminiExpress BeadChip, HumanExome, or OmniExpressExome BeadChip. A genotype imputation was carried out using Minimac algorithm with the reference panel using WGS data of the biobank Japan project (N=1,037) and 1KGP p3v5 ALL (N=2,504). Then, a genome-wide association study (about 20,000,000 imputed variants) for height was performed (BOLT-LMM [ver2.2] and mach2qtl).
hum0014.v14
A total of 165,436 participants whose smoking status is available were genotyped by using of Illumina HumanOminiExpress BeadChip, HumanExome, or OmniExpressExome BeadChip. A genotype imputation was carried out using Minimac algorithm with the 1000 genomes Phase I v3 release as a reference. Then, a genome-wide association study (about 6,000,000 imputed SNVs) was performed (BOLT-LMM and ProbABEL program).
hum0014.v13
Result of meta analysis of following 4 GWASs (txt file) .
- 9,804 T2DM patients and 6,728 controls
- 5,639 T2DM patients and 19,407 controls
- 18,688 T2DM patients and 121,950 controls
- 2,483 T2DM patients and 7,065 controls
Genotypes were determined by using of Illumina [HumanOmniExpress, HumanExome, OmniExpressExome, Human610-Quad BeadChip].
hum0014.v12
Result of meta analysis of following 2 GWASs (csv file).
- 2,380 T2DM with diabetic nephropathy patients and 5,234 T2DM without diabetic nephropathy patients
- 429 T2DM with diabetic nephropathy patients and 358 T2DM without diabetic nephropathy patients
Genotypes were determined by using of OmniExpressExome Beadchip or Human610-Quad BeadChip [Illumina].
hum0014.v11
A target capture sequencing analysis of 11 hereditary breast cancer genes in 7,104 breast cancer patients and 23,731 controls was performed. Fastq files are provided.
hum0014.v10
Whole genome sequencing analysis for a total of 1,026 patients, who were registered Bio Bank Japan from 2003 - 2007 was performed. Fastq files are provided.
hum0014.v9
A total of 67,029 females with information on age at menarche and 43,861 females with information on age at menopause were genotyped by using of Illumina HumanOminiExpress BeadChip, HumanExome, or OmniExpressExome BeadChip. A genotype imputation was carried out using Minimac algorithm with the 1000 genomes Phase I v3 release as a reference. Then, a genome-wide association study (about 10,000,000 imputed SNVs) was performed (mach2dat program).
hum0014.v8
A total of 162,255 patients, who were registered Bio Bank Japan from 2003 - 2007 were genotyped by using of Illumina HumanOminiExpress-12 BeadChip, HumanExome, or OmniExpressExome BeadChip. A genotype imputation was carried out using Minimac algorithm with the 1000 genomes Phase I v3 release as a reference. Then, genome-wide association studies (about 6,000,000 imputed SNVs) were performed (mach2qtl program).
hum0014.v7
A total of 3980 patients with primary open-angle glaucoma and 18,815 controls were genotyped by using of Illumina HumanOminiExpress BeadChip, HumanExome, or OmniExpressExome BeadChip. A genotype imputation was carried out using Minimac algorithm with the 1000 genomes Phase I v3 release as a reference. Then, a genome-wide association study (about 6,000,000 imputed SNVs) was performed (mach2dat program).
hum0014.v6
A total of 158,284 patients, who were registered Bio Bank Japan from 2003 - 2007 were genotyped by using of Illumina HumanOminiExpress-12 BeadChip, HumanExome, or OmniExpressExome BeadChip. A genotype imputation was carried out using Minimac algorithm with the 1000 genomes Phase I v3 release as a reference. Then, a genome-wide association study (about 6,000,000 imputed SNVs) was performed (mach2qtl program).
hum0014.v5
A total of 8180 patients with atrial fibrillation, who were registered Bio Bank Japan from 2003 - 2007, and 28,612 controls were genotyped by using of Illumina HumanOminiExpress-12 BeadChip, HumanExome, or OmniExpressExome BeadChip (900,000 SNVs). A genotype imputation was carried out using Minimac algorithm with the 1000 genomes Phase I v3 release as a reference. Then, a genome-wide association study (5,000,000 imputed SNVs) was performed (mach2dat program).
hum0014.v4
A total of 1472 patients with atopic dermatitis and 7966 controls were genotyped by using of Illumina HumanOminiExpress-12 BeadChip (606,164 SNVs). A genotype imputation was carried out using Minimac algorithm with the 1000 genomes Phase I v3 release as a reference. Then, a genome-wide association study (7,700,000 imputed SNVs) was performed using logic regression tests with imputed SNP dosage data (mach2dat program).
hum0014.v3
GWASs for T2DM were performed using 552,915 SNPs (9817 T2DM patients vs 6763 controls) and 479,088 SNPs (5646 T2DM patients vs 19,420 controls). Allele frequencies of T2DM patients and controls were compared.
Genotypes were determined by using of OmniExpressExome Beadchip or Human610-Quad BeadChip [Illumina], respectively.
hum0014.v2
Genotype frequencies of 934 healthy individuals, about 190 patients from each of 35 diseases, 182 esophageal cancer patients, and 92 ALS patients.
35 diseases:
Cancer (Lung cancer, Breast cancer, Gastric cancer, Colorectal cancer, Prostate cancer)
Cardiovascular diseases (Heart failure, Myocardial infarction, Unstable angina, Stable angina, Cardiac arrhythmias, Arteriosclerosis obliterans)
Cerebrovascular disorders (Brain infarction, Intracranial aneurysm)
Respiratory tract diseases (Interstitial pneumonitis & pulmonary fibrosis, Pulmonary emphysema, Bronchial asthma)
Chronic liver diseases (Chronic hepatitis C, Liver cirrhosis)
Eye diseases (Cataract, Glaucoma)
Others (Epilepsy, Periodontal disease, Urolithiasis, Nephrotic syndrome, Uterine myoma, Endometriosis, Osteoporosis, Rheumatoid arthritis, Amyotrophic lateral sclerosis, Hay fever, Atopic dermatitis, Drug eruptions , Hyperlipidemias, Diabetes mellitus, Basedow disease)
Illumina [Human610-Quad BeadChip, HumanHap550v3 Genotyping BeadChip], Perlegen Sciences [high-density oligonucleotide arrays], or Hologic Japan [Invader] were used for the genotyping.
hum0014.v1
A Genome-Wide Association Study (GWAS) for MI was performed using 455,781 SNPs (Illumina Human610-Quad BeadChip and HumanHap550v3 Genotyping BeadChip). Allele frequencies of 1666 MI patients and 3198 controls were compared.
Note：
hum0201.v8_release note
hum0201 Release Note
| Research ID | Release Date | Type of Data |
|---|---|---|
| hum0201.v8 | 2024/08/28 | NGS (Exome, RNA-seq, scRNA-seq, ATAC-seq, ChIP-seq) |
| hum0201.v7 | 2022/12/27 | Processed data of JGAD000335 by JGA |
| hum0201.v6 | 2022/08/05 | NGS (scRNA-seq, RNA-seq, Exome) |
| hum0201.v5 | 2022/06/06 | NGS (RNA-seq) |
| hum0201.v4 | 2021/11/19 | NGS (RNA-seq, ChIP-seq) |
| hum0201.v3 | 2020/11/20 | NGS (RNA-seq) |
| hum0201.v2 | 2020/10/06 | NGS (WGS, RNA-seq) |
| hum0201.v1 | 2019/12/20 | NGS (Exome) |
hum0201.v8
DNAs/RNAs extracted from pancreatic cancer organoids or genetically engineered pancreatic duct organoids were used for the whole exome, RNA, scRNA, ATAC and ChIP sequencing analyses. Fastq and bed files are provided.
hum0201.v7
The alignment results [CRAM], variant call results per sample [gVCF], and variant call results per dataset [aggregated VCF] processed JGAD000335 in a certain workflow were provided. If you plan to use the data, please indicate both original data (JGAD000335) and processed data (JGAD000687) on the application form for data use.
hum0201.v6
RNAs extracted from normal colonic tissue from a neoplastic disease patient was used for the single cell RNA sequencing analysis. DNAs and RNAs extracted from organoids established from healthy normal colonic tissues of the patients were used for the whole genome and RNA sequencing analyses. Fastq files are provided.
hum0201.v5
RNAs extracted from organoids derived from colon cancer tissues from neoplastic disease patients were used for the RNA sequencing analysis. Fastq files are provided.
hum0201.v4
DNAs and RNAs extracted from organoids established from colon cancer tissues and a normal epithelial tissue of the patients were used for RNA sequencing and ChIP-seq analyses. Fastq files are provided.
hum0201.v3
Gene expression of 2D normal duodenum organoids with or without medium rotation was analyzed. Total RNA was extracted from organoids with or without a four-day medium rotation, and after 0, 1, 2 or 4 days of medium rotation, and sequenced with HiSeq X Ten. Fastq files are provided.
hum0201.v2
DNAs and RNAs extracted from peripheral blood cells and organoids established from normal and cancer tissues of the patients were used for the whole genome and RNA sequencing analysis. Fastq files are provided.
hum0201.v1
DNAs extracted from inflammatory/tumor tissues from gastrointestinal inflammatory disease patients, peripheral blood cells from patients/controls, and the organoids established from epithelial tissues from patients were used for the whole exome sequencing analysis. Fastq files are provided.
Note：
hum0201.v8
NBDC Research ID: hum0201.v8
SUMMARY
Aims: Search for differences in genomics and traits among normal cells, digestive non-tumor cells (inflammatory cells), and tumor cells
Methods:
JGAS000199: The organoids were established from epithelial tissues from patients, and cultured. DNAs were extracted from the organoids and peripheral blood cells. Whole exome sequencing analysis was performed to identify the somatic mutations.
JGAS000237: Organoids were established from tissue samples (normal and cancer) obtained from any cancer patients. The organoids were cultured, and DNA / RNA was extracted from the organoids for whole genome / RNA sequencing analysis to identify the somatic mutations. Blood samples were substituted when normal tissue samples were not available.
JGAS000256: RNA was extracted from the 2D-cultured normal duodenal organoids with or without medium rotation. RNA sequencing was performed to identify the changes in gene expression after culture medium rotation.
JGAS000378: RNA sequencing and Chip-seq analysis for the organoids derived from colon cancer tissues and a normal epithelial tissue from patients
JGAS000350: RNA sequencing analysis for the organoids derived from colon cancer tissues
JGAS000550: single cell RNA sequencing analysis for normal colonic tissue and RNA sequencing or Whole Exome sequencing analyses for the organoids derived from healthy normal colonic tissues in the neoplastic disease patient
JGAS000719: Organoids were derived from surgically resected specimens, endoscopic ultrasound-guided fine needle aspiration samples, brushing samples, pleural effusion, and ascites of patients with pancreatic cancer. Genetically engineered human pancreatic duct organoids were made by introducing cancer gene mutations in duct organoids using CRISPR-Cas9. DNAs/RNAs were extracted from the organoids for whole exome sequencing, RNA sequencing, single cell RNA sequencing, ATAC sequencing, and ChIP sequencing analyses.
Participants/Materials:
JGAS000199: Controls who underwent colonoscopy, gastrointestinal inflammatory disease patients, and neoplastic disease patients
JGAS000237: Neoplastic disease patients
JGAS000256: Normal duodenum tissue from a neoplastic disease patient
JGAS000378: Colon cancer tissues and a normal epithelial tissue from neoplastic disease patients
JGAS000350: Neoplastic disease patient
JGAS000550: Neoplastic disease patient
JGAS000719: Pancreatic cancer patients
| Dataset ID | Type of Data | Criteria | Release Date |
|---|---|---|---|
| JGAS000199 | NGS (Exome) | Controlled-access (Type I) | 2019/12/20 |
| JGAS000237 | NGS (WGS, RNA-seq) | Controlled-access (Type I) | 2020/10/06 |
| JGAS000256 | NGS (RNA-seq) | Controlled-access (Type I) | 2020/11/20 |
| JGAS000378 | NGS (RNA-seq, ChIP-seq) | Controlled-access (Type I) | 2021/11/19 |
| JGAS000350 | NGS (RNA-seq) | Controlled-access (Type I) | 2022/06/06 |
| JGAS000550 | NGS (scRNA-seq, RNA-seq, Exome) | Controlled-access (Type I) | 2022/08/05 |
| JGAD000687 | Processed data of JGAD000335 by JGA | Controlled-access (Type I) | 2022/12/27 |
| JGAS000719 | NGS（Exome, RNA-seq, scRNA-seq, ATAC-seq, ChIP-seq） | Controlled-access (Type I) | 2024/08/28 |
*Data users need to apply an application for Using NBDC Human Data to reach the Controlled-access Data. Learn more
MOLECULAR DATA
Exome (JGAS000199/JGAS000550/JGAS000719)
| Participants/Materials |
gastrointestinal inflammatory disease (ICD10: K51): 29 cases gastrointestinal inflammatory disease with neoplastic disease (ICD10: K51, C18, C19, C20): 26 cases organoids derived from healthy normal colonic tissues with neoplastic disease (ICD10: C18): 2 cases controls who underwent colonoscopy: 16 individuals pancreatic cancer (ICD10: C25): 50 cases (organoids derived from tumor tissues） |
| Targets | Exome |
| Target Loci for Capture Methods | - |
| Platform | Illumina [HiSeq 2500/4000, NovaSeq6000] |
| Library Source | DNAs extracted from peripheral blood cells and organoids established from normal or inflammatory/tumor tissues of the patients or controls |
| Cell Lines | - |
| Library Construction (kit name) | SureSelect Human All Exon kit |
| Fragmentation Methods | Ultrasonic fragmentation |
| Spot Type | Paired-end |
| Read Length (without Barcodes, Adaptors, Primers, and Linkers) | 200 bp |
| Japanese Genotype-phenotype Archive Dataset ID | |
| Total Data Volume |
JGAD000284: 488 GB (fastq) JGAD000669: 59.5 GB (fastq) JGAD000852：846.3 GB（fastq） |
| Comments (Policies) | NBDC policy |
| Participants/Materials |
Neoplastic disease: 23 cases (55 samples) Small cell lung cancer (ICD10: C34) Biliary tract cancer (ICD10: C23, C24, C78) Colon cancer (ICD10: C18-20) Duodenal cancer (ICD10: C17) Esophageal cancer (ICD10: C15) Stomach cancer (ICD10: C16, C78) Liver cancer (ICD10: C22) Pancreatic cancer (ICD10: C25) |
| Targets | WGS |
| Target Loci for Capture Methods | - |
| Platform | Illumina [HiSeq X Ten] |
| Library Source | DNAs extracted from peripheral blood cells and organoids established from normal and cancer tissues of the patients |
| Cell Lines | - |
| Library Construction (kit name) | Library was constructed by BGI |
| Fragmentation Methods | Ultrasonic fragmentation |
| Spot Type | Paired-end |
| Read Length (without Barcodes, Adaptors, Primers, and Linkers) | 300 bp |
| Japanese Genotype-phenotype Archive Dataset ID | |
| Dataset ID of the Processed data by JGA | |
| Total Data Volume | 2.752 TB (fastq) |
| Comments (Policies) | NBDC policy |
RNA-seq (JGAS000237, JGAS000378)
| Participants/Materials |
Neoplastic disease: 23 + 4 cases (35+ 5 samples) Small cell lung cancer (ICD10: C34) Biliary tract cancer (ICD10: C23, C24, C78) Colon cancer (ICD10: C18-20) Duodenal cancer (ICD10: C17) Esophageal cancer (ICD10: C15) Stomach cancer (ICD10: C16, C78) Liver cancer (ICD10: C22) Pancreatic cancer (ICD10: C25) |
| Targets | RNA-seq |
| Target Loci for Capture Methods | - |
| Platform | Illumina [HiSeq 2500/X Ten, NovaSeq 6000] |
| Library Source |
RNAs extracted from organoids established from tumor tissues and a normal epithelial tissue of the patients RNAs extracted from organoids with BET bromodomain inhibitor established from tumor tissues and a normal epithelial tissue of colon cancer patients |
| Cell Lines | - |
| Library Construction (kit name) |
TruSeq RNA Library Prep Kit v2 TruSeq Stranded mRNA Library Prep Kit |
| Fragmentation Methods | Heat treatment |
| Spot Type | Paired-end |
| Read Length (without Barcodes, Adaptors, Primers, and Linkers) | 250 bp/150 bp |
| Japanese Genotype-phenotype Archive Dataset ID | |
| Total Data Volume |
JGAD000336: 2.752 TB (fastq) JGAD000492: 190.5 GB (fastq) |
| Comments (Policies) | NBDC policy |
| Participants/Materials | Neoplastic disease (ICD10: C16): 1 case (1 sample) |
| Targets | RNA-seq |
| Target Loci for Capture Methods | - |
| Platform | Illumina [HiSeq X Ten] |
| Library Source | Total RNA extracted from normal duodenum organoids with or without a four-day medium rotation, and after 0, 1, 2 or 4 days of medium rotation |
| Cell Lines | - |
| Library Construction (kit name) |
TruSeq RNA Library Prep Kit v2 TruSeq Stranded mRNA Library Prep Kit |
| Fragmentation Methods | Heat treatment |
| Spot Type | Paired-end |
| Read Length (without Barcodes, Adaptors, Primers, and Linkers) | 250 bp/150 bp |
| Japanese Genotype-phenotype Archive Dataset ID | JGAD000359 |
| Total Data Volume | 37 GB (fastq) |
| Comments (Policies) | NBDC policy |
| Participants/Materials | Neoplastic disease (ICD10: C16): 2 case (11 sample) |
| Targets | RNA-seq |
| Target Loci for Capture Methods | - |
| Platform | Illumina [HiSeq 4000] |
| Library Source | RNAs extracted from organoids derived from colon cancer tissues |
| Cell Lines | - |
| Library Construction (kit name) |
TruSeq RNA Library Prep Kit v2 TruSeq Stranded mRNA Library Prep Kit |
| Fragmentation Methods | Heat treatment |
| Spot Type | Paired-end |
| Read Length (without Barcodes, Adaptors, Primers, and Linkers) | 250 bp/150 bp |
| Japanese Genotype-phenotype Archive Dataset ID | JGAD000464 |
| Total Data Volume | 108.9 GB (fastq) |
| Comments (Policies) | NBDC policy |
| Participants/Materials | Neoplastic disease (ICD10: C18): 2 case (8 sample) |
| Targets | RNA-seq |
| Target Loci for Capture Methods | - |
| Platform | Illumina [NovaSeq 6000] |
| Library Source | Total RNA extracted from normal duodenum organoids with or without a four-day medium rotation, and after 0, 1, 2 or 4 days of medium rotation |
| Cell Lines | - |
| Library Construction (kit name) |
TruSeq RNA Library Prep Kit v2 TruSeq Stranded mRNA Library Prep Kit |
| Fragmentation Methods | Heat treatment |
| Spot Type | Paired-end |
| Read Length (without Barcodes, Adaptors, Primers, and Linkers) | 150 x 2 bp |
| Japanese Genotype-phenotype Archive Dataset ID | JGAD000669 |
| Total Data Volume | 46.6 GB (fastq) |
| Comments (Policies) | NBDC policy |
| Participants/Materials |
Pancreatic cancer (ICD10: C25): 40 case (50 sample) organoids derived from tumor tissues: 38 cases (38 samples) genetically engineered pancreatic duct organoids: 2 cases (12 samples) |
| Targets | RNA-seq |
| Target Loci for Capture Methods | - |
| Platform | Illumina [HiSeq 4000, NovaSeq 6000] |
| Library Source | RNAs extracted from pancreatic cancer organoids or genetically engineered pancreatic duct organoids |
| Cell Lines | - |
| Library Construction (kit name) |
TruSeq RNA Library Prep Kit v2 TruSeq Stranded mRNA Library Prep Kit |
| Fragmentation Methods | Heat treatment |
| Spot Type | Paired-end |
| Read Length (without Barcodes, Adaptors, Primers, and Linkers) | 150 x 2 bp |
| Japanese Genotype-phenotype Archive Dataset ID | JGAD000852 |
| Total Data Volume | 846.3 GB (fastq) |
| Comments (Policies) | NBDC policy |
| Participants/Materials | Neoplastic disease (ICD10: C16): 1 case (1 sample) |
| Targets | scRNA-seq |
| Target Loci for Capture Methods | - |
| Platform | Illumina [HiSeq 4000] |
| Library Source | RNAs extracted from organoids from normal colonic tissue |
| Cell Lines | - |
| Library Construction (kit name) | Single Cell 3′ Library & Gel Bead Kit v2 and the A Chip Kit (10X Genomics) |
| Fragmentation Methods | Enzymatic fragmentation |
| Spot Type | Paired-end |
| Read Length (without Barcodes, Adaptors, Primers, and Linkers) | 28+91 bp |
| Japanese Genotype-phenotype Archive Dataset ID | JGAD000669 |
| Total Data Volume | 66.0 GB (fastq) |
| Comments (Policies) | NBDC policy |
| Participants/Materials |
Pancreatic cancer (ICD10: C25): 1 case (6 sample) (genetically engineered pancreatic duct organoids) |
| Targets | scRNA-seq |
| Target Loci for Capture Methods | - |
| Platform | Illumina [HiSeq 4000] |
| Library Source | RNAs extracted from genetically engineered pancreatic duct organoids |
| Cell Lines | - |
| Library Construction (kit name) | Chromium Next GEM Single Cell 3’ Reagent Kits v3.1 |
| Fragmentation Methods | Enzymatic fragmentation |
| Spot Type | Paired-end |
| Read Length (without Barcodes, Adaptors, Primers, and Linkers) | 28+91 bp |
| Japanese Genotype-phenotype Archive Dataset ID | JGAD000852 |
| Total Data Volume | 846.3 GB (fastq) |
| Comments (Policies) | NBDC policy |
| Participants/Materials |
Neoplastic disease: 4 cases (5 samples) Colon cancer (ICD10: C18) |
| Targets | ChIP-seq |
| Target Loci for Capture Methods | - |
| Platform | Illumina [HiSeq X Ten] |
| Library Source | DNAs extracted from organoids derived from colon cancer tissues and a normal epithelial tissue of the patients, and immunoprecipitated with an anti-histone antibody (H3K27Ac) |
| Cell Lines | - |
| Library Construction (kit name) | Illumina Tagment DNA TDE1 Enzyme and Buffer Kits |
| Fragmentation Methods | Ultrasonic fragmentation (Bioruptor Ⅱ) |
| Spot Type | Paired-end |
| Read Length (without Barcodes, Adaptors, Primers, and Linkers) | 150 bp |
| Japanese Genotype-phenotype Archive Dataset ID | JGAD000492 |
| Total Data Volume | 190.5 GB (fastq) |
| Comments (Policies) | NBDC policy |
| Participants/Materials |
Pancreatic cancer (ICD10: C25): 5 case (13 sample) organoids derived from tumor tissues: 3 cases (3 samples) genetically engineered pancreatic duct organoids: 2 cases (10 samples) |
| Targets | ChIP-seq |
| Target Loci for Capture Methods | - |
| Platform | Illumina [HiSeq X Ten] |
| Library Source | DNAs extracted from pancreatic cancer organoids or genetically engineered pancreatic duct organoids, and immunoprecipitated with an anti-histone antibody (H3K27me3) |
| Cell Lines | - |
| Library Construction (kit name) | Illumina Tagment DNA TDE1 Enzyme and Buffer Kits |
| Fragmentation Methods | Ultrasonic fragmentation (Bioruptor Ⅱ) |
| Spot Type | Paired-end |
| Read Length (without Barcodes, Adaptors, Primers, and Linkers) | 150 bp |
| QC | FRiP score |
| Mapping Methods | Bowtie2 |
| Reference Genome Sequence | hg38 |
| Peak Calling Methods (software) | MACS2 |
| Japanese Genotype-phenotype Archive Dataset ID | JGAD000852 |
| Total Data Volume | 882.8 GB (fastq, bed) |
| Comments (Policies) | NBDC policy |
| Participants/Materials |
Pancreatic cancer (ICD10: C25): 12 cases (16 samples) organoids derived from tumor tissues: 10 cases (12 samples) genetically engineered pancreatic duct organoids: 2 cases (4 samples) |
| Targets | ATAC-seq |
| Target Loci for Capture Methods | - |
| Platform | Illumina [HiSeq X Ten] |
| Library Source | DNAs extracted from pancreatic cancer organoids or genetically engineered pancreatic duct organoids |
| Cell Lines | - |
| Library Construction (kit name) | Omni-ATAC protocol |
| Fragmentation Methods | Tn5 transposase |
| Spot Type | Paired-end |
| Read Length (without Barcodes, Adaptors, Primers, and Linkers) | 150 x 2 bp |
| Japanese Genotype-phenotype Archive Dataset ID | JGAD000852 |
| Total Data Volume | 846.3 GB (fastq) |
| Comments (Policies) | NBDC policy |
DATA PROVIDER
Principal Investigator: Toshiro Sato
Affiliation: Department of Organoid Medicine, Keio University School of Medicine
Project / Group Name: -
Funds / Grants (Research Project Number):
| Name | Title | Project Number |
|---|---|---|
| Project for Elucidating and Controlling Mechanisms of Aging and Longevity, Japan Agency for Medical Research and Development (AMED) | Understanding changes in aging traits aimed at controlling the onset of gastrointestinal diseases | JP19gm5010002 |
| Project for Cancer Research and Therapeutic Evolution (P-CREATE), Japan Agency for Medical Research and Development (AMED) | Development of advanced drug discovery system based on understanding of cancer multi-level phenotype | JP19cm0106206 |
| Core Research and Evolutional Science and Technology, Advanced Research & Development Programs for Medical Innovation, Japan Agency for Medical Research and Development (AMED-CREST) | Dissecting intestinal fibrogenic diseases by a newly developed 4D disease model system | JP19gm1210001 |
| KAKENHI Grant-in-Aid for Scientific Research (S) | Gaining Integrative Understanding of Gastrointestinal Disease Phenotypes through Establishment of an Organoid Library | 17H06176 |
| KAKENHI Grant-in-Aid for Scientific Research (B) | Functional analysis of small intestinal epithelial organoid-based transplant graft | 20H03746 |
| KAKENHI Grant-in-Aid for Scientific Research (S) | Elucidating a role of niche construction in pathophysiological mechanism of human digestive diseases | 22H04995 |
PUBLICATIONS
| Title | DOI | Dataset ID | |
|---|---|---|---|
| 1 | Somatic inflammatory gene mutations in human ulcerative colitis epithelium | doi: 10.1038/s41586-019-1844-5 | JGAD000284 |
| 2 | An Organoid Biobank of Neuroendocrine Neoplasms Enables Genotype-Phenotype Mapping | doi: 10.1016/j.cell.2020.10.023 |
JGAD000335 JGAD000336 |
| 3 | An organoid-based organ repurposing approach to treat short bowel syndrome | doi: 10.1038/s41586-021-03247-2 | JGAD000359 |
| 4 | Organoid screening reveals epigenetic vulnerabilities in human colorectal cancer | doi: 10.1038/s41589-022-00984-x | JGAD000492 |
| 5 |
USRES (Controlled-access Data)
| Principal Investigator | Affiliation | Country/Region | Research Title | Data in Use (Dataset ID) | Period of Data Use |
|---|---|---|---|---|---|
| Klaus H. Kaestner | Institue for Diabetes, Obesity & Metabolism at Unversity of Pennsylvania | Somatic mutation analysis of the pancreas in type 1 diabetes | JGAD000284 | 2020/04/13-2021/03/03 | |
| Ulf Leser | Department of Mathematics and Computer Science, Humboldt-Universitaet zu Berlin | MAPTor-NET: MAPK-mTOR network model driven individualized therapies of pancreatic neuro-endocrine tumors (pNETs) | JGAD000335, JGAD000336 | 2021/06/03-2023/04/01 | |
| Nobuhiro Tanuma | Miyagi Cancer Center Research Institute | Japan | Study on biological characters of pancreatic and gastrointestinal neuroendocrine tumors using patient-derived organoids. | JGAD000336 | 2022/09/19-2023/07/31 |
| Michiaki Hamada | Faculty of Science and Engineering, Waseda University | Japan | Construction of RNA-targeted Drug Discovery Database | JGAD000336, JGAD000359, JGAD000492 | 2022/12/26-2025/03/31 |
hum0474.v1
NBDC Research ID: hum0474.v1
SUMMARY
Aims: Autism Spectrum Disorders (ASDs) are psychiatric disorders with a high prevalence and a significant genetic component. The aetiology is still unknown and there are still no fundamental treatments. The aim of this study was to investigate the presence or absence of variants (mutations or polymorphisms) in genes associated with the onset and transition of the condition in children with autistic spectrum disorder and their families, to examine the relationship between genetic variants and the clinical phenotype (clinical condition), and to use this information for diagnosis, treatment and support.
Methods: Based on the SFARI gene database, 16 highly confident ASD-associated genes, one promoter region, and 20 intergenic regions containing ASD-associated SNPs were selected for the biotinylated oligonucleotide probe design. For sequencing, buccal mucosa was collected using a swab. Genomic DNA extracted from the buccal mucosa samples were used for Target Capture Sequencing analysis.
Participants/Materials: 32 children with ASD, 8 children with low birth weight, 3 children with sub-threshold ASD, 36 typically developing children
URL: https://kodomokokoro.w3.kanazawa-u.ac.jp/en/
| Dataset ID | Type of Data | Criteria | Release Date |
|---|---|---|---|
| JGAS000731 | NGS (Target Capture) | Controlled-access (Type I) | 2024/08/22 |
* Data users need to apply an application for Using NBDC Human Data to reach the Controlled-access Data. Learn more
MOLECULAR DATA
| Participants/Materials |
32 children with ASD (ICD10: F849) 8 children with low birth weight 3 children with sub-threshold ASD 36 typically developing children buccal mucosa: each 1 sample (total 79 samples) |
| Targets | Target Capture |
| Target Loci for Capture Methods |
ASD-associated genes: POGZ, SCN1A, SCN2A, FOXP1, SLC6A1, ARID1B, SYNGAP1, CNTNAP2, KCNQ3, PTEN, SUV420H1, GRIN2B, CHD8, ADNP, DYRK1A, SHANK3 Promoter region: HTTLPR SNPs in intergenic regions: rs1620977, rs34213746, rs1452075, rs16854048 , rs325506, rs2388334, rs111931861, rs7794745, rs10099100, rs11787216, rs2094530, rs10149470, rs113877277, rs6035856, rs6035857, rs6047381, rs6137325, rs6137326, rs71190156, rs910805 |
| Platform | Illumina [iSeq 100] |
| Library Source | DNAs extracted from buccal mucosa samples |
| Cell Lines | - |
| Library Construction (kit name) | KAPA HyperPlus Kit |
| Fragmentation Methods | Enzymatic fragmentation |
| Spot Type | Paired-end |
| Read Length (without Barcodes, Adaptors, Primers, and Linkers) | 150 bp |
| Mapping Methods | Burrows-Wheeler Aligner v0.7.17 |
| Mapping Quality | - |
| Reference Genome Sequence | GRCh38 |
| Coverage (Depth) | - |
| Japanese Genotype-phenotype Archive Dataset ID | JGAD000864 |
| Total Data Volume | 4.5 GB (fastq, vcf) |
| Comments (Policies) | NBDC policy |
DATA PROVIDER
Principal Investigator: Shigeru Yokoyama
Affiliation: Research Center for Child Mental Development, Kanazawa University
Project / Group Name: Bambi Plan
URL: https://kodomokokoro.w3.kanazawa-u.ac.jp/en/
Funds / Grants (Research Project Number):
| Name | Title | Project Number |
|---|---|---|
| KAKENHI Grant-in-Aid for JSPS Fellows | Establishment of diagnostic indices of sub-threshold autism spectrum disorder by brain function imaging and genomic analyses | 22J14602 |
| KAKENHI Grant-in-Aid for Scientific Research (B) | A study of symptom variability corresponding to functional features of brain activity in children with autism spectrum disorder | 20H03599 |
| KAKENHI Grant-in-Aid for Scientific Research (B) | study of biological investigation of autism spectrum disorder including sub-threshold | 23K27526 |
PUBLICATIONS
USRES (Controlled-access Data)
| Title | DOI | Dataset ID | |
|---|---|---|---|
| 1 | Association of Genetic Variants with Autism Spectrum Disorder in Japanese Children Revealed by Targeted Sequencing | doi: 10.3389/fgene.2024.1352480 | JGAD000864 |
| 2 |
| Principal Investigator | Affiliation | Country/Region | Research Title | Data in Use (Dataset ID) | Period of Data Use |
|---|---|---|---|---|---|
