README.md

In SharonLutz/RNAseqRare: Runs the RNAseqRare Function

RNAseqRare

The RNAseqRare R package performs expression quantitative trait loci (eQTL) analyses of rare variants for RNA-seq data.

Installation

install.packages("devtools") # The devtools package must be installed first
install.packages("MASS") # The MASS package must be installed first
install.packages("SKAT") # The SKAT package must be installed first

devtools::install_github("SharonLutz/RNAseqRare")

Example

For the given dataset dataR, one can test if the read counts (i.e. Y) are associated with a collection of rare variants (i.e. X). The code below runs this analysis.

library(RNAseqRare)
?RNAseqRare # For details on this function and how to choose input variables

data("dataR")
y<-dataR[,"y"] 
x<-dataR[,1:124]
RNAseqRare(x,y)

Output

For this analysis, the rare variants in the region (i.e. X) are associated with the given read counts (i.e. Y) for all 3 methods: method 1 using SKAT with the normalized count data, method 2 using a negative binomial regression with the sum of rare variants in the region, and method 3 using a negative binomial regression with an indicator for rare variants in the region.

$`p-value from SKAT with normalized count data`
[1] 0.04538739

$`negative binomial with sum of rare variants`
              Estimate Std. Error   z value     Pr(>|z|)
(Intercept) 2.57019238  0.1457844 17.630096 1.447218e-69
xSum        0.06925349  0.0382376  1.811136 7.011982e-02

$`negative binomial with indicator for rare variants`
             Estimate Std. Error   z value     Pr(>|z|)
(Intercept) 2.3978953  0.2182372 10.987562 4.386143e-28
xI          0.4629861  0.2514543  1.841234 6.558733e-02

Note

As recomended in the paper, the SKAT (SKAT, SKAT-O, and SKAT-Burden) methods using the normalized read counts worked best in the simulation scenarios that were considered in the paper below.

Reference

Lutz SM, Thwing A, Fingerlin TE. (2019) eQTL mapping of rare variant associations using RNA-seq data: An evaluation of approaches. PLoS One.

SharonLutz/RNAseqRare documentation built on Oct. 7, 2019, 6:28 a.m.