Previous characterizations of allelic ratios using RNA-Seq are subject to a number of caveats, most notably high read depth requirements [ 29- 31] and underrepresentation of variant versus reference alleles [ 32, 33] resulting from alignment algorithms penalizing variant alleles as mismatching errors when compared to the reference genome.
Depth of coverage is also considered during scoring penalizing variants with higher-than expected coverage.
Although PeRC does not always outperform other methods, its improved performance over the sparse group lasso is encouraging for rare variant penalized regression.
In this work, we formulate and comparatively evaluate four relatively simple procedures for such fusion based on Fisher estimation and its conditional bias-penalized variant: Direct Estimation (DE), Bias Correction (BC), Reduced-Dimension Bias Correction (RBC) and Simple Estimation (SE).
However, evaluating the accuracy of nucleotide corrections based on the available reference sequence can be misleading, as haplotype variants may be penalized and therefore the number of false-positive/negative corrections inflated.
For instance, we may choose to penalize the common variants based on their MAF and set equal to, which results in when, as implemented in the software Mendel [Zhou et al., 44, 2011].
With weights based on minor allele frequencies for the group and common coefficients, we find that we may lose power to detect common variants as they are more heavily penalized.
Of note, unlike switch errors the standard method to calculate phasing error rates where an incorrect haplotype block is penalized only once, we estimate error by testing each variant independently and therefore our error rate represents worst-case scenario.
To account for length polymorphisms that maintain the coding frame and hence represent true biological variants, any small gap comprising a multiple of three nucleotides is not penalized.
As we relax the error rate, penalized methods outperform the ATT in detection, and may be useful for further exploration of causal variants.
