run_lm: A wrapper for deciding either to run a default lm or a...

In syyang93/analyzeR: This package contains functions that Stephanie uses for her analysis of recount RNAseq data.

Description

formula: Expr ~ SCORE + Cov, where Cov = covariates

Usage

run_lm(expr, cov, SCORE, omit.outlier = T, method = "default")

Arguments

expr	Expression vector (numeric) with length = #samples
cov	Regression covariates in form [cov x samples]
SCORE	The PRS, not included in 'cov'
omit.outlier	Whether or not you want to omit gene expression outliers
method	Choose between 'default' or 'two-stage' for lm() method (see desc. in support functions below)

Details

Runs linear regression to estimate effect of SCORE on gene expression

Value

A [1 x 8] vector output from an lm() like below: ['intercept', 'beta', 'SE', 't_value', 'pval', 'beta.conf.low', 'beta.conf.high', 'corr.rho']

Author: Vamsee Pillalamarri

syyang93/analyzeR documentation built on Aug. 26, 2020, 4:34 p.m.