Dataset ID

NHA000190

Name: NHA000190: GWAS for gut microbiome, GWAS for plasma metabolite, GWAS for KEGG Gene Ortholog and KEGG Pathway
Published: 2023-10-02

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

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641–660 / 732

File	Label	Size
microbiome_L7_species_Prevotella_buccalis_QCed_sumstats.tsv.gz	Prevotella_buccalis	524 MB
microbiome_L7_species_Prevotella_copri_QCed_sumstats.tsv.gz	Prevotella_copri	523 MB
microbiome_L7_species_Prevotella_corporis_QCed_sumstats.tsv.gz	Prevotella_corporis	524 MB
microbiome_L7_species_Prevotella_disiens_QCed_sumstats.tsv.gz	Prevotella_disiens	524 MB
microbiome_L7_species_Prevotella_marshii_QCed_sumstats.tsv.gz	Prevotella_marshii	524 MB
microbiome_L7_species_Prevotella_multiformis_QCed_sumstats.tsv.gz	Prevotella_multiformis	525 MB
microbiome_L7_species_Prevotella_nanceiensis_QCed_sumstats.tsv.gz	Prevotella_nanceiensis	525 MB
microbiome_L7_species_Prevotella_oris_QCed_sumstats.tsv.gz	Prevotella_oris	522 MB
microbiome_L7_species_Prevotella_sp_QCed_sumstats.tsv.gz	Prevotella_sp	522 MB
microbiome_L7_species_Prevotella_stercorea_QCed_sumstats.tsv.gz	Prevotella_stercorea	524 MB
microbiome_L7_species_Prevotella_timonensis_QCed_sumstats.tsv.gz	Prevotella_timonensis	525 MB
microbiome_L7_species_Proteobacteria_bacterium_QCed_sumstats.tsv.gz	Proteobacteria_bacterium	525 MB
microbiome_L7_species_Pseudoflavonifractor_capillosus_QCed_sumstats.tsv.gz	Pseudoflavonifractor_capillosus	527 MB
microbiome_L7_species_Pseudoflavonifractor_sp_QCed_sumstats.tsv.gz	Pseudoflavonifractor_sp	525 MB
microbiome_L7_species_Raoultella_ornithinolytica_QCed_sumstats.tsv.gz	Raoultella_ornithinolytica	526 MB
microbiome_L7_species_Raoultella_planticola_QCed_sumstats.tsv.gz	Raoultella_planticola	525 MB
microbiome_L7_species_Riemerella_columbina_QCed_sumstats.tsv.gz	Riemerella_columbina	525 MB
microbiome_L7_species_Rikenella_microfusus_QCed_sumstats.tsv.gz	Rikenella_microfusus	524 MB
microbiome_L7_species_Romboutsia_sp_QCed_sumstats.tsv.gz	Romboutsia_sp	521 MB
microbiome_L7_species_Roseburia_faecis_QCed_sumstats.tsv.gz	Roseburia_faecis	522 MB

641–660 / 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
Data use policy: NBDC data sharing policy (JGAP000001)