NBDC Research ID: hum0014.v30
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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. Whole-genome sequencing analyses for 1,026 patients, who were registered Bio Bank Japan from 2003 - 2007, 1,765 myocardial infarction patients and 199 dementia 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 |
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* 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
| 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. 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) | 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.. |
| Total Data Volume | 73 TB (fastq) + 49 TB (bam, vcf) |
| 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 |
| 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=1,026) - 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 |
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 |
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 |
| 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 |
