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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481–500 / 732

File	Label	Size
microbiome_L7_species_Corynebacterium_durum_QCed_sumstats.tsv.gz	Corynebacterium_durum	525 MB
microbiome_L7_species_Corynebacterium_sp_QCed_sumstats.tsv.gz	Corynebacterium_sp	524 MB
microbiome_L7_species_Cryptobacterium_sp_QCed_sumstats.tsv.gz	Cryptobacterium_sp	524 MB
microbiome_L7_species_Culturomica_massiliensis_QCed_sumstats.tsv.gz	Culturomica_massiliensis	525 MB
microbiome_L7_species_Dakarella_massiliensis_QCed_sumstats.tsv.gz	Dakarella_massiliensis	525 MB
microbiome_L7_species_Desulfotomaculum_sp_QCed_sumstats.tsv.gz	Desulfotomaculum_sp	524 MB
microbiome_L7_species_Desulfovibrio_desulfuricans_QCed_sumstats.tsv.gz	Desulfovibrio_desulfuricans	526 MB
microbiome_L7_species_Desulfovibrio_piger_QCed_sumstats.tsv.gz	Desulfovibrio_piger	524 MB
microbiome_L7_species_Desulfovibrio_sp_QCed_sumstats.tsv.gz	Desulfovibrio_sp	523 MB
microbiome_L7_species_Dialister_invisus_QCed_sumstats.tsv.gz	Dialister_invisus	523 MB
microbiome_L7_species_Dialister_sp_QCed_sumstats.tsv.gz	Dialister_sp	521 MB
microbiome_L7_species_Dialister_succinatiphilus_QCed_sumstats.tsv.gz	Dialister_succinatiphilus	526 MB
microbiome_L7_species_Dielma_fastidiosa_QCed_sumstats.tsv.gz	Dielma_fastidiosa	523 MB
microbiome_L7_species_Dorea_formicigenerans_QCed_sumstats.tsv.gz	Dorea_formicigenerans	525 MB
microbiome_L7_species_Dorea_longicatena_QCed_sumstats.tsv.gz	Dorea_longicatena	523 MB
microbiome_L7_species_Dorea_sp_QCed_sumstats.tsv.gz	Dorea_sp	522 MB
microbiome_L7_species_Drancourtella_massiliensis_QCed_sumstats.tsv.gz	Drancourtella_massiliensis	526 MB
microbiome_L7_species_Eggerthella_lenta_QCed_sumstats.tsv.gz	Eggerthella_lenta	523 MB
microbiome_L7_species_Eggerthella_sp_QCed_sumstats.tsv.gz	Eggerthella_sp	522 MB
microbiome_L7_species_Eisenbergiella_massiliensis_QCed_sumstats.tsv.gz	Eisenbergiella_massiliensis	526 MB

481–500 / 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)