README.md

In maialab/daeqtlr: DAEQTL Mapping

daeqtlr

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

maialab/daeqtlr documentation built on May 18, 2022, 6:53 a.m.