bio-causal-genomics-pleiotropy-detection skillA
bio-causal-genomics-pleiotropy-detection is agent-read markdown (skill) from pku-yuangroup/openai4s: Detect and adjust for horizontal pleiotropy in two-sample Mendelian randomization by distinguishing uncorrelated (UHP) from correlated (CHP) pleiotropy and choosing among Egger, MR-PRESSO, MR-RAPS, CAUSE, LHC-MR, LCV, MR-Clust, MR-Mix, and contamination-mixture methods. Use when validating an MR causal claim, running the STROBE-MR sensitivity battery, suspecting a shared heritable confounder, working under weak-instrument or polygenic-exposure regimes, or reconciling discordant estimates across .
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What the file says
## Version Compatibility
Reference examples tested with: TwoSampleMR 0.5.11+, MendelianRandomization 0.9.0+, MR-PRESSO 1.0+, CAUSE 1.2.0+, MR-Clust 0.1.0+, MRMix 0.1+, mr.raps 0.4.1+ (GitHub), LHC-MR 0.0.0.9000+ (GitHub), LCV (script-based, no version tag), simex 1.8+.
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# Pleiotropy Detection in Mendelian Randomization
**"Validate my MR result against pleiotropic bias"** -> Decompose violations of the exclusion-restriction assumption into uncorrelated horizontal pleiotropy (UHP, addressable by Egger / median / mode / MR-PRESSO) and correlated horizontal pleiotropy (CHP, addressable only by CAUSE / LHC-MR / LCV), then run a method battery whose assumptions span both regimes.
- R: `TwoSampleMR::mr()` (IVW + Egger + median + mode), `mr_pleiotropy_test()`, `mr_heterogeneity()`, `mr_leaveoneout()`, `directionality_test()`
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Source
pku-yuangroup/openai4s · 586 stars · license MIT · pushed 2026-09-23 · branch main
API
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