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bio-causal-genomics-transcriptome-wide-association

Performs gene-level association from GWAS summary statistics via genetically predicted tissue expression using FUSION, PrediXcan, S-PrediXcan, S-MultiXcan, UTMOST, MOSTWAS, kTWAS, EpiXcan, TIGAR-V2, and probabilistic fine-mapping with FOCUS and MA-FOCUS. Use when running TWAS from GWAS sumstats, prioritising candidate causal genes from a GWAS lead locus, picking single-tissue vs cross-tissue model

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Atualizado há 4 meses

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Version Compatibility

Reference examples tested with: FUSION (head of gusevlab/fusion_twas, scripts dated 2023+), MetaXcan / S-PrediXcan / S-MultiXcan 0.7.5+ (hakyimlab/MetaXcan), PrediXcan model files from PredictDB (GTEx v8 elastic-net + MASHR), UTMOST (head of Joker-Jerome/UTMOST), pyfocus 0.8+ (bogdanlab/focus), MA-FOCUS (head of mancusolab/ma-focus), TIGAR-V2 (head of yanglab-emory/TIGAR), PLINK 1.9 + PLINK 2.0, R 4.3+, Python 3.9-3.11.

Before using code patterns, verify in

[Description truncada. Veja o README completo no GitHub.]

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