MendelianRandomization: an R package for performing Mendelian randomization analyses using summarized data

MendelianRandomization: an R package for performing Mendelian randomization analyses using summarized data

MendelianRandomization is a software package for the R open-source software environment that performs Mendelian randomization analyses using summarized data. The core functionality is to implement the inverse-variance weighted, MR-Egger and weighted median methods for multiple genetic variants. Several options are available to the user, such as the use of robust regression, fixed- or random-eff...

MendelianRandomization v0.2.2: an R package for performing Mendelian randomization analyses using summarized data

• betaX and betaXse are both numeric vectors describing the associations of the genetic variants with the exposure. betaX are the beta-coefficients from univariable regression analyses of the exposure on each genetic variant in turn, and betaXse are the standard errors. • betaY and betaYse are both numeric vectors describing the associations of the genetic variants with the outcome. betaY are t...

Mendelian Randomization Analysis With Multiple Genetic Variants Using Summarized Data

Genome-wide association studies, which typically report regression coefficients summarizing the associations of many genetic variants with various traits, are potentially a powerful source of data for Mendelian randomization investigations. We demonstrate how such coefficients from multiple variants can be combined in a Mendelian randomization analysis to estimate the causal effect of a risk fa...

BITE: an R package for biodiversity analyses

Nowadays, molecular data analyses for biodiversity studies often require advanced bioinformatics skills, preventing many life scientists from analyzing their own data autonomously. BITE R package provides complete and user-friendly functions to handle SNP data and third-party software results (i.e. Admixture, TreeMix), facilitating their visualization, interpretation and use. Furthermore, BITE ...

Running Head: Mendelian Randomization Using Genetic Information to Infer Causality in Observational Data: Mendelian Randomization