For samples with high mean read depth, variants were called using quality-based variant detection in CLC Genomics Workbench with a minimum read depth of 40x, minimum average quality of 20, and minimum required variant count of 2 present on both the forward and the reverse reads with a strand bias interval between 20-80% [ 20, 34].
The Minimum Variant Read Count filter excluded variants that occurred in less than three (for SNPs) or two (for indels) reads when summed across all GDP VCF files.
The rationale for implementing a "Minimum variant read count" filter twice in the pipeline (Steps 1 and 6) is as follows.
To classify whether mismatches were sequencing errors or genomic variations, parameters were set as follows: minimum depth, 30; minimum variant frequency, 35%; least mismatch count, 20; and homo/heterozygote fold change, 2. RAP-DB was utilized to locate the discovered SNPs.
This was done under the assumption that the minimum frequency observed corresponds to a variant count of 1.
A variant count on a minimum of two reads was required with the variant present in both forward and reverse reads and a strand bias within a 20%-80 20%-80val.
Single-nucleotide polymorphism (SNP) candidates were screened using the CLC Genomics Workbench 5.1 with the following parameters: window length, 11; maximum gap and mismatch count, 3; minimum coverage, 1; minimum variant frequency, 75%.
Under the criteria of minimum coverage (read depth) of four and the minimum variant frequency of two, the variations compared to the reference sequence were counted as SNPs.
Parameters were as follows: neighborhood radius = 5, maximum gap and mismatch count = 2, minimum neighborhood quality = 15, minimum central quality = 20, minimum coverage = 10, and minimum variant frequency = 35.0.
An optional minimum variant support, v, used in extending ambiguity.
