RILStEp

RILStEp(Recombinant Inbred Lines Stepwise Epistasis analysis) package is the epistasis analysis tool. This package enables to detect the epistatic relationships between SNPs for RIL population by comparison of 2 models based on bayes factor.
publication: https://doi.org/10.1093/g3journal/jkab130

Requirements

Other than CRAN package, GWASpoly package is required for RILStEp package.
please install it.

install.packages("devtools")
devtools::install_github("jendelman/GWASpoly", build_vignettes=FALSE)

Installation

You can install RILStEp from GitHub with:

# install.packages("devtools")
devtools::install_github("slt666666/RILStEp")

Example

This is a basic example script:

library(RILStEp)

### loading dataset
loaded_data <- load_data("phenotype.csv", "genotype.csv", "trait1")

### check all combinations of 2 SNPs
result1 <- rilstep(loaded_data, "result1", core_num = 8)

### using 1 SNP in each 500 SNPs
result2 <- rilstep(loaded_data, "result2", interval = 500)

### specify QTL-like SNPs by user.
result3 <- rilstep(loaded_data, "result3", qtls = c("chr08_19928351", "chr09_3909046"))

### specify No QTLs.
result4 <- rilstep(loaded_data, "result3", qtls = FALSE)

### using SNPs in specific regions
result5 <- rilstep(loaded_data, "result4", region = c("chr03_2132221:chr10_9330401", "chr03_2132221:chr10_9330401"))

### consider heterozygous
result6 <- rilstep(loaded_data, "result5", heterozygous = TRUE)

### example
result7 <- rilstep(loaded_data, "result6", interval = 500, region = c("chr03_2132221:chr10_9330401", "chr03_2132221:chr10_9330401"), core_num = 8)

option region=c() can specify regions. rilstep check all combinations of SNPs in specified regions.

region = c("chr03_1234")                                    # chr03_1234 x all SNPs
region = c("chr03_1234:chr10_5678")                         # chr03_1234 ~ chr10_5678 x all SNPs
region = c("chr03_1234", "chr10_5678")                      # chr03_1234 x chr10_5678
region = c("chr03_1234:chr10_5678", "chr04_9012:chr7_3456") # chr03_1234~chr10_5678 x chr04_9012~chr7_3456

Input data format

input files should be csv format.

phenotype data

Name	trait1
Sample1	12.3
Sample2	23.4
…	…
SampleXX	78.9

genotype data

Marker	Chrom	Position	Sample1	Sample2	…	SampleXX
1	chr01	1234	2	2	…	2
2	chr01	3456	2	0	…	0
3	chr01	9999	0	0	…	1
…	…	…	…	…	…
XXX	chr12	4869786	0	0	…	2

marker coded as {0,1,2} = {AA,AB,BB}
A, B: each parental genotype
!! Only bi-allelic markers are allowed !!