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Dataset ID

NHA000190

Type of data
GWAS for gut microbiome
GWAS for plasma metabolite
GWAS for KEGG Gene Ortholog and KEGG Pathway
Access criteria
Unrestricted-access
Total data volume
320 GB
File formats
  • TSV
  • DOCX
Research
hum0197
Date published
2023-10-02
Date modified
2023-10-02
Secondary ID
hum0197.v18.gwas.v1

Unrestricted-access files linked to this dataset

Per page
20

141–160 / 732

FileLabelSizeCopy URL
metabo_C_0130_QCed_sumstats.tsv.gzAsymmetric dimethylarginine319 MB
metabo_C_0131_QCed_sumstats.tsv.gzSymmetric dimethylarginine318 MB
metabo_C_0133_QCed_sumstats.tsv.gzO-Acetylcarnitine318 MB
metabo_C_0134_QCed_sumstats.tsv.gzTrp318 MB
metabo_C_0136_QCed_sumstats.tsv.gzKynurenine319 MB
metabo_C_0137_QCed_sumstats.tsv.gz3-Methoxytyrosine319 MB
metabo_C_0138_QCed_sumstats.tsv.gzXC0061318 MB
metabo_C_0141_QCed_sumstats.tsv.gzXC0065318 MB
metabo_C_0142_QCed_sumstats.tsv.gzN-Acetylgalactosamine;N-Acetylmannosamine;N-Acetylglucosamine318 MB
metabo_C_0143_QCed_sumstats.tsv.gzCystathionine318 MB
metabo_C_0146_QCed_sumstats.tsv.gzIsobutyrylcarnitine319 MB
metabo_C_0147_QCed_sumstats.tsv.gzButyrylcarnitine319 MB
metabo_C_0148_QCed_sumstats.tsv.gzCystine318 MB
metabo_C_0153_QCed_sumstats.tsv.gzUridine318 MB
metabo_C_0158_QCed_sumstats.tsv.gzDyphylline318 MB
metabo_C_0165_QCed_sumstats.tsv.gz1-Methyladenosine318 MB
metabo_C_0167_QCed_sumstats.tsv.gzOctanoylcarnitine318 MB
metabo_C_0168_QCed_sumstats.tsv.gzArgininosuccinic acid318 MB
metabo_C_0169_QCed_sumstats.tsv.gzXC0120318 MB
metabo_C_0170_QCed_sumstats.tsv.gzGlutathione (GSSG)_divalent319 MB

141–160 / 732

Analysis method

genome wide SNPs

Materials and participants
524 Japanese individuals (423 species in the gut microbiome)
306 Japanese individuals (306 plasma metabolites)
524 Japanese individuals (KEGG Gene Ortholog and KEGG Pathway)
  • Subject count
    524 (Individual)
  • Population
    Japanese
Sample description
DNAs extracted from peripheral blood cells
  • Tissue
    Peripheral blood
  • Tumor / normal
    Normal
Experimental method
Genotyping by array
WGS
Reagent kit
Infinium Asian Screening Array Kit
KAPA Hyper Prep Kit
TruSeq DNA PCR-Free Library Prep Kit
Platform
Illumina HiSeq 2500
Illumina HiSeq 3000
Illumina HiSeq X
Illumina Infinium Asian Screening Array
Illumina NovaSeq 6000
Reference genome
GRCh37
QC and filtering
SNP array data:
Sample QC: We excluded individuals with low genotyping call rates (call rate < 98%). We included individuals of the estimated Asian ancestry using PCA.
Variant QC: We excluded variants with (1) genotyping call rate < 99%, (2) minor allele count < 5, (3) P-value for Hardy-Weinberg equilibrium < 1.0 × 10^−10, and (4) > 5% allele frequency difference compared with the imputation reference panel or the allele frequency panel of Tohoku Medical Megabank Project.
Post-imputation QC: We excluded imputed variants with Rsq < 0.7 and minor allele frequency < 1%.
WGS:
We excluded variants with genotype call rate <90%, ExcessHet > 60, Hardy-Weinberg P<1.0×10−10
After imputation with Beagle v5.1, we excluded imputed variants with minor allele frequency < 1%.
Imputation
Haplotype phasing: shapeit4
Imputation: minimac4
Analysis method
SNP array:
Genotyping: GenomeStudio
WGS:
WA-MEM v0.7.13 + GATK v3.8-0
PLINK2
Variant count
Gut microbiota/KEGG (SNP array): 7,213,470 variants
Blood metabolites (WGS): 6,840,258 variants
Processed data type
GWAS summary statistics
Phenotype data
Included