pyTWMR: transcriptome-wide Mendelian randomization in python.
Details
Serval ID
serval:BIB_975C14D52EEC
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
pyTWMR: transcriptome-wide Mendelian randomization in python.
Journal
Bioinformatics
ISSN
1367-4811 (Electronic)
ISSN-L
1367-4803
Publication state
Published
Issued date
02/08/2024
Peer-reviewed
Oui
Volume
40
Number
8
Language
english
Notes
Publication types: Journal Article
Publication Status: ppublish
Publication Status: ppublish
Abstract
Mendelian randomization (MR) is a widely used approach to estimate causal effect of variation in gene expression on complex traits. Among several MR-based algorithms, transcriptome-wide summary statistics-based Mendelian Randomization approach (TWMR) enables the uses of multiple SNPs as instruments and multiple gene expression traits as exposures to facilitate causal inference in observational studies.
Here we present a Python-based implementation of TWMR and revTWMR. Our implementation offers GPU computational support for faster computations and robust computation mode resilient to highly correlated gene expressions and genetic variants.
pyTWMR is available at github.com/soreshkov/pyTWMR.
Here we present a Python-based implementation of TWMR and revTWMR. Our implementation offers GPU computational support for faster computations and robust computation mode resilient to highly correlated gene expressions and genetic variants.
pyTWMR is available at github.com/soreshkov/pyTWMR.
Keywords
Mendelian Randomization Analysis/methods, Transcriptome/genetics, Polymorphism, Single Nucleotide, Software, Algorithms, Humans
Pubmed
Web of science
Open Access
Yes
Create date
19/08/2024 9:21
Last modification date
05/09/2024 9:00