Extract a vector of allelic expression ratios

ae() provides a handy shortcut to extract a vector of allelic expression ratios for a DAE SNP on a set of samples.

ae_hom() and ae_het() also extract a vector of allelic expression ratios but for the corresponding homozygous or heterozygous samples of the candidate SNP, respectively.

Usage

ae(dae_snp, ae, samples = rep(TRUE, ncol(ae) - 1), drop_na = TRUE)

ae_hom(dae_snp, candidate_snp, zygosity, ae, drop_na = TRUE)

ae_het(dae_snp, candidate_snp, zygosity, ae, drop_na = TRUE)

Arguments

dae_snp: A string indicating the identifier of the DAE SNP.
ae: A data frame of expression values. Each row is for a locus. The locus identity is indicated in the first column. Remaining columns are samples.
samples: Either a logical or an integer vector indicating which samples in the ae data table are to be selected.
drop_na: Whether to drop NA values in the returned value.
candidate_snp: A string indicating the identifier of the candidate SNP.
zygosity: A data frame of zygosity levels: "hom" for homozygous or "het" for heterozygous. Each row is for a locus. The locus identity is indicated in the first column and named snp. Remaining columns are samples.

Value

A numeric vector of allelic ratios.

Examples

# Let us load some dummy data
zygosity <- read_snp_zygosity(file = daeqtlr_example("zygosity.csv"))
ae <- read_ae_ratios(file = daeqtlr_example("ae.csv"))

# Select all allelic expression ratios of rsX019
ae('rsX019', ae = ae, drop_na = FALSE)
#>  [1]          NA          NA          NA          NA          NA          NA
#>  [7] -0.78121260          NA          NA -0.19801280 -0.27931810          NA
#> [13]          NA          NA          NA -0.92423460 -0.03798342  0.03065449
#> [19]          NA  0.10446470          NA          NA          NA          NA
#> [25]          NA          NA          NA -0.23169140          NA          NA
#> [31]          NA          NA -0.32567110          NA          NA          NA
#> [37]          NA          NA          NA -0.15817040          NA -0.44861720
#> [43]          NA          NA          NA  0.09732815          NA          NA
#> [49]          NA          NA

# Select only the first 5 samples
ae('rsX019', ae = ae, samples = 1:10, drop_na = FALSE)
#>  [1]         NA         NA         NA         NA         NA         NA
#>  [7] -0.7812126         NA         NA -0.1980128
ae('rsX019', ae = ae, samples = 1:10, drop_na = TRUE)
#> [1] -0.7812126 -0.1980128

# Use a logical vector to select samples that meet a requirement, e.g.
# heterozygous samples only. Note that `is_het()` is useful here.
(het_samples_for_rsX019 <- is_het(zygosity = zygosity, snp = 'rsX019'))
#>  [1] FALSE FALSE FALSE FALSE FALSE FALSE  TRUE FALSE FALSE  TRUE  TRUE FALSE
#> [13]  TRUE FALSE FALSE  TRUE  TRUE  TRUE FALSE  TRUE FALSE FALSE FALSE FALSE
#> [25] FALSE FALSE FALSE  TRUE FALSE FALSE FALSE FALSE  TRUE FALSE FALSE FALSE
#> [37] FALSE FALSE FALSE  TRUE FALSE  TRUE FALSE FALSE FALSE  TRUE FALSE FALSE
#> [49] FALSE FALSE
ae('rsX019', ae = ae, samples = het_samples_for_rsX019, drop_na = FALSE)
#>  [1] -0.78121260 -0.19801280 -0.27931810          NA -0.92423460 -0.03798342
#>  [7]  0.03065449  0.10446470 -0.23169140 -0.32567110 -0.15817040 -0.44861720
#> [13]  0.09732815

# If you want the allelic ratios for samples that are simultaneously:
# - heterozygous for rsX019
# - homozygous for rsX002
(hom_samples_for_rsX002 <- is_hom(zygosity = zygosity, snp = 'rsX002'))
#>  [1]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE  TRUE
#> [13]  TRUE  TRUE  TRUE  TRUE  TRUE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE
#> [25]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE
#> [37]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE FALSE  TRUE  TRUE  TRUE
#> [49]  TRUE FALSE
ae(
  dae_snp = 'rsX019',
  ae = ae,
  samples = het_samples_for_rsX019 & hom_samples_for_rsX002,
  drop_na = FALSE
  )
#>  [1] -0.78121260 -0.19801280          NA -0.92423460 -0.03798342  0.10446470
#>  [7] -0.23169140 -0.32567110 -0.15817040 -0.44861720  0.09732815

# Or more simply:
ae_hom('rsX019', 'rsX002', zygosity, ae, drop_na = FALSE)
#>  [1] -0.78121260 -0.19801280          NA -0.92423460 -0.03798342  0.10446470
#>  [7] -0.23169140 -0.32567110 -0.15817040 -0.44861720  0.09732815

# Compare with the previous
ae_hom('rsX019', 'rsX002', zygosity, ae, drop_na = TRUE)
#>  [1] -0.78121260 -0.19801280 -0.92423460 -0.03798342  0.10446470 -0.23169140
#>  [7] -0.32567110 -0.15817040 -0.44861720  0.09732815