The goal of daeqtlr is to perform differential allelic expression trait loci (DAEQTL) mapping.
Differential allelic expression (DAE) can be treated as a quantitative trait. Marker genotypes collected from the same set of individuals can, in turn, be used in testing statistical associations with DAE. This package provides routines for performing such a workflow, i.e. DAEQTL mapping.
Learn more in https://maialab.org/daeqtlr.
Installation
You can install the development version of daeqtlr like so:
# install.packages("remotes")
remotes::install_github("maialab/daeqtlr")Usage
Here’s a quick example on how to perform DAEQTL mapping with daeqtlr. For more details about this example read vignette("daeqtlr").
library(daeqtlr)
# SNP pairs to be tested for statistical association
snp_pairs <- read_snp_pairs(file = daeqtlr_example("snp_pairs.csv"))
# Zygosity levels (homozygous or heterozygous) for genotyped SNPs
zygosity <- read_snp_zygosity(file = daeqtlr_example("zygosity.csv"))
# Allelic expression (AE) ratios of DAE SNPs
ae <- read_ae_ratios(file = daeqtlr_example("ae.csv"))
mapping_dt <-
daeqtl_mapping(snp_pairs = snp_pairs,
zygosity = zygosity,
ae = ae)
# Here's the first 30 SNP pairs tested
mapping_dt[1:30, -c('dae_snp_position', 'candidate_snp_position')]
#> dae_snp candidate_snp chromosome pvalue case
#> 1: rsX019 rsX002 19 0.8331668 4
#> 2: rsX019 rsX003 19 0.1348031 4
#> 3: rsX019 rsX005 19 0.9280741 4
#> 4: rsX019 rsX010 19 0.9280741 4
#> 5: rsX019 rsX014 19 0.1348031 4
#> 6: rsX019 rsX016 19 NA 2
#> 7: rsX019 rsX017 19 NA 2
#> 8: rsX019 rsX018 19 0.9255817 4
#> 9: rsX019 rsX022 19 0.3994533 4
#> 10: rsX019 rsX023 19 0.3736310 4
#> 11: rsX019 rsX024 19 0.8813157 4
#> 12: rsX019 rsX025 19 NA 1
#> 13: rsX019 rsX026 19 NA 1
#> 14: rsX019 rsX043 19 NA 1
#> 15: rsX019 rsX045 19 NA 2
#> 16: rsX019 rsX046 19 NA 1
#> 17: rsX019 rsX047 19 NA 2
#> 18: rsX019 rsX048 19 NA 2
#> 19: rsX019 rsX050 19 NA 2
#> 20: rsX019 rsX051 19 NA 2
#> 21: rsX019 rsX053 19 NA 2
#> 22: rsX019 rsX054 19 NA 2
#> 23: rsX019 rsX060 19 0.1348031 4
#> 24: rsX019 rsX064 19 NA 1
#> 25: rsX020 rsX008 1 0.1226391 4
#> 26: rsX020 rsX011 1 0.1003482 3
#> 27: rsX020 rsX012 1 0.1003482 3
#> 28: rsX020 rsX013 1 NA 1
#> 29: rsX020 rsX015 1 0.3492677 4
#> 30: rsX020 rsX021 1 0.1814492 3
#> dae_snp candidate_snp chromosome pvalue case