ecco: Controlling for Confounding Effects in eQTL Mapping Studies...

In fanyue322/ECCO: Controlling for Confounding Effects in eQTL Mapping Studies through Joint Differential Expression and Mendelian Randomization Analyses

Description

Determining the optimal number of PEER factors for eQTL mapping analysis through DE and MR analysis

Usage

ecco(pheno, gene, gene_name, iv_snp, peer, summary)

Arguments

pheno	the phenotype data
gene	a matrix containing the whole gene expression data after removing the PEER factors
gene_name	a vector containg the names of all genes
iv_snp	the instrumental variable, produced from ecco0
peer	the number of peer factors to be examined
summary	the effect size estiamted when the number of PEER is 0, produced from ecco0 or ecc0_ivw

Details

Instead of performing repetitive eQTL mapping, ECCO jointly applies differential expression analysis and Mendelian randomization (MR) analysis, leading to substantial computational savings.

Value

Gene	the name of the gene
PEER	the number of PEER factors
p-value	the p-value of alpha
beta_hat	the estimation of beta from MR model
beta_tilde	the estimation of beta from DE model

Examples

data(exampledata)
attach(exampledata)
num_peer=1
summary<-ecco(Y,peer[[num_peer]],gene_name,iv_snp,num_peer,summary)
closeAllConnections()
detach(exampledata)

fanyue322/ECCO documentation built on July 11, 2020, 1:10 p.m.