README.md

In 2eding/MTVR: R version of MultiTrans

MTVR

R version of MultiTrans (http://genetics.cs.ucla.edu/multiTrans/)

Prerequistes for running Source Code

(suggest using Linux environment)

Usage

Step 1. Install and load package

library(devtools) install_github("2eding/MTVR") library(MTVR)

Step 2. Input data

X <- as.matrix(data.table::fread("X_rightdim.txt")) (individual x SNP) Y <- as.matrix(data.table::fread("Y.txt")) (Phenotype x individual) data.table::fread <= This package is useful for input large data X_rightdim.txt is snp data * Y.txt is gene expression data

Step 3. Calculate the kinship

K <- Kinship(X, outPath, outName)

Step 4. Calculate the variance components

VC <- varComp(Y, K, numThreads, outPath, outName) (numThreads = Determines how many threads to use)

Step 5. Estimate correlation in the rotated space

corrMatrix <- generateR(X, K, VC, outPath, outName) covBandMatrix <- generateC(windowSize, corrMatrix, outPath = "./", outName = "c.txt")

Step 6. Run SLIDE

step1 <- system.file('./slide_1prep', package='MTVR') step2 <- system.file('./slide_2run', package='MTVR') step3 <- system.file('./slide_3sort', package='MTVR') step4 <- system.file('./slide_4correct', package='MTVR') system(paste(step1, "-C", "covBandMat path", windowSize, "outPath & outName")) system(paste(step2, "step1's outPath & outName", "outPath & outName", simulationNum, seedNum)) system(paste(step3, "outPath & outName", "step2's outPath & outName")) system(paste(step4, "-p", "step2's outPath & outName", "threshold file path", "outPath & outName"))

2eding/MTVR documentation built on Sept. 3, 2020, 11:51 a.m.