List of known SNP positions (based on SNP chip data) for base quality score recalibration of alignments for whole-genome resequencing and whole-genome bisulfite sequencing data from great tits (Parus major)

The profiling of epigenetic marks like DNA methylation has become a
central aspect of studies in evolution and ecology. Bisulfite sequencing
is commonly used for assessing genome-wide DNA methylation at single
nucleotide resolution but these data can also provide information on
genetic variants like single nucleotide polymorphisms (SNPs). However,
bisulfite conversion causes unmethylated cytosines to appear as thymines,
complicating the alignment and subsequent SNP calling. Several tools have
been developed to overcome this challenge, but there is no independent
evaluation of such tools for non-model species, which often lack genomic
references. Here, we used whole-genome bisulfite sequencing (WGBS) data
from four female great tits (Parus major) to evaluate the performance of
seven tools for SNP calling from bisulfite sequencing data. We used SNPs
from whole-genome resequencing data of the same samples as baseline SNPs
to assess common performance metrics like sensitivity, precision, and the
number of true positive, false positive, and false negative SNPs for the
full range of variant and genotype quality values. We found clear
differences between the tools in either optimizing precision (Bis-SNP),
sensitivity (biscuit), or a compromise between both (all other tools).
Overall, the choice of SNP caller strongly depends on which performance
parameter should be maximized and whether ascertainment bias should be
minimized to optimize downstream analysis, highlighting the need for
studies that assess such differences.