The function to calculate allele median ratios, proportion of heterozygotes and allele probability values under different assumptions (see details), and their chi-square significance values for duplicate detection
Usage
allele.info(
X,
x.norm = NULL,
method = c("MedR", "QN", "pca", "TMM", "TMMex"),
logratioTrim = 0.3,
sumTrim = 0.05,
Weighting = TRUE,
Acutoff = -1e+10,
plot.allele.cov = TRUE,
verbose = TRUE,
...
)Arguments
- X
allele depth table generated from the function
hetTgen(non-normalized)- x.norm
a data frame of normalized allele coverage, output of
cpm.normal. If not provided, calculated usingX.- method
character. method to be used for normalization (see
cpm.normaldetails). DefaultTMM- logratioTrim
numeric. percentage value (0 - 1) of variation to be trimmed in log transformation
- sumTrim
numeric. amount of trim to use on the combined absolute levels (“A” values) for method
TMM- Weighting
logical, whether to compute (asymptotic binomial precision) weights
- Acutoff
numeric, cutoff on “A” values to use before trimming
- plot.allele.cov
logical, plot comparative plots of allele depth coverage in homozygotes and heterozygotes
- verbose
logical, whether to print progress
- ...
further arguments to be passed to
plot
Value
Returns a data frame of median allele ratio, proportion of heterozygotes, number of heterozygotes, and allele probability at different assumptions with their chi-square significance
Details
Allele information generated here are individual SNP based and presents the proportion of heterozygotes, number of samples, and deviation of allele detection from a 1:1 ratio of reference and alternative alleles. The significance of the deviation is tested with Z-score test \(Z = \frac{ \frac{N}{2}-N_A}{ \sigma_{x}}\), and chi-square test (see references for more details on the method).
References
McKinney, G. J., Waples, R. K., Seeb, L. W., & Seeb, J. E. (2017). Paralogs are revealed by proportion of heterozygotes and deviations in read ratios in genotyping by sequencing data from natural populations. Molecular Ecology Resources, 17(4)
Karunarathne et al. 2022 (to be added)
Examples
if (FALSE) data(ADtable)
AI<-allele.info(ADtable,x.norm=ADnorm)
#> calculating probability values of alleles
#>
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#> calculating chi-square significance
#>
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#> assessing excess of heterozygotes
#>
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