Terry-Liu88's Stars
precimed/mixer
Causal Mixture Model for GWAS summary statistics
xinhe-lab/multigroup_ctwas
multigroup version of cTWAS package
856tangbin/PCMR
Pleiotropic Clustering of Mendelian Randomization
cumc/pecotmr
Pair-wise enrichment, colocalization, TWAS and Mendelian Randomization to integrate molecular QTL and GWAS.
HDTian/TVMR
Time-varying Mendelian randomization
winston779/flyingbird
flyingbird官网地址
wangzhen89/GLMM
MRCIEU/ukbb-prot-prs
aj-grant/mrcovreg
zhonghualiu/MRMiSTERI
Robust Mendelian Randomization Analysis with Invalid IVs
noahlorinczcomi/simmrd
Generate simulation data to use in univariable or multivariable Mendelian Randomization simulations
CYShapland/BESIDEMR
BayEsian Set IDEntification Mendelian randomization
ZixuanWu1/MrMediation
An R package for Mendelian Randomization in Mediation setting
danieliong/MRPATH
R package for investigating heterogeneous causal mechanisms in Mendelian Randomization
noahlorinczcomi/MRBEE
Mendelian Randomization with Bias-corrected Estimating Equations
massimoaria/pubmedR
Gathering metadata about publications, patents, grants, clinical trials and policy documents from PubMed database
jrs95/geni.plots
GENI plots to visualise results from genome-wide association studies
jean997/cause
R package for CAUSE
jean997/GWASBrewer
Simulate GWAS data from an arbitrary DAG
remlapmot/GWASBrewer
Simulate GWAS data from an arbitrary DAG
noahlorinczcomi/HORNET
Tool to perform genome-wide multivariable Mendelian Randomization using xQTL GWAS summary statistics
YuxiaoRuoyao/mrScan
Automatically Select Heritable Confounders for Mendelian Randomization
amandaforde/winnerscurse_MR
Removing Winner’s Curse bias in two-sample Mendelian randomisation with summary data
YangLabHKUST/MR-APSS
Mendelian Randomization accounting for Pleiotropy and Sample Structure using genome-wide summary statistics
jingshuw/GRAPPLE
An R package for Mendelian Randomization
MRCIEU/temmpo
Text mining for mechanism prioritisation
MRCIEU/CAMERA
Mendelian Randomization approach using Cross Ancestral Model
jianyanglab/gsmr2
The gsmr R-package implements the GSMR (Generalised Summary-data-based Mendelian Randomisation) method that uses GWAS summary statistics to test for a putative causal association between two phenotypes (e.g., a modifiable risk factor and a disease) based on a multi-SNP model
Vinnish-A/transGI
houlstonlab/MR-PheWAS
Code for MR-PheWAS paper