Version Compatibility

Reference examples tested with: TwoSampleMR 0.6.0+, MendelianRandomization 0.10+, MR-PRESSO 1.0+, cause 1.2+, MVMR 0.4+, ieugwasr 1.0+, MRlap 0.0.3.2+, coloc 5.2+, mrclust 0.1+, lhcMR 0.0.1+, R 4.4+. Both TwoSampleMR 0.6.0 and ieugwasr 1.0 are the JWT-transition versions; older versions still expect deprecated OAuth.

Before using code patterns, verify installed versions match. If versions differ:

• R: packageVersion('<pkg>') then ?function_name to verify parameters
• CLI (plink, GCTA-GSMR): <tool> --version then <tool> --help

If code throws an error referencing a function that has moved (e.g. ieugwasr::ld_clump vs TwoSampleMR::clump_data) or an OAuth token failure, introspect the installed API and adapt the example rather than retrying.

Mendelian Randomization

"Test whether trait X causally affects trait Y from GWAS summary statistics" -> Use genetic variants as instrumental variables (IVs) that satisfy three assumptions (relevance, independence, exclusion restriction) to estimate beta_causal = beta_outcome / beta_exposure under the IV framework (Davey Smith & Ebrahim 2003 IJE 32:1; Burgess & Thompson 2021 Chapman & Hall/CRC, 2nd ed.). Tool choice is a decision about the regime (one-sample vs two-sample, sparse vs polygenic, drug-target vs polygenic exposure) and the pleiotropy model (balanced, directional InSIDE, correlated horizontal). Wrong tool inflates Type-I error or attenuates true effects in a direction predictable from the bias structure.

• R: TwoSampleMR::mr() orchestrates IVW + Egger + weighted median + weighted mode in one call
• R: MendelianRandomization::mr_ivw / mr_egger / mr_median / mr_mbe / mr_conmix per-method API (S4 objects; MR-RAPS is NOT in this package -- use TwoSampleMR::mr_raps() which wraps the GitHub mr.raps)
• R: MRPRESSO::mr_presso() global / outlier / distortion tests
• R: cause::cause() correlated horizontal pleiotropy mixture
• R: MVMR::strength_mvmr() + MVMR::ivw_mvmr() multivariable conditional-F + IVW