Read Stacks batch_ files
(.tags.tsv.gz, .snps.tsv.gz and .sumstats.tsv) to produce templates for
high-throughput genotyping. Within locus consensus sequences, template
candidates are filtered and central SNPs are identified based on minimum flank
sizes and other options. Consensus sequences containing central SNPs that
fulfill a few quality criteria are then used to create sequences in which the
central SNP is called out and SNPs in flanking regions are assigned IUPAC
codes.
Apart from standard modules, this requires the Perl module Statistics::Distributions.
Example output:
locus_0005448 TAACAGCTGGCTCCTCGGCGCTCAACCATCAACGTCCATCATCTCCGAGT[C/T]CTCCACCTCAGTATACTCCTCCCCGTCCTCAATCCTCGTACCCTCGGCAT
locus_0007269 AACATGTTGCTTTCCCCTCCTCTTTTATTTATGCAGCTTGACAAATGGCT[A/G]CACATAATGGTGTCAATTCGCCTCGATAATTTCACTTTGAGCATGCGGGC
locus_0007492 AATGAAGGAGAAAGGGGAGGAGGAAGACTTGTAGGTCACAGCCACAGCCA[A/G]GGTAAGTCCAAAAAATTGTTCTCTCGTTTTTTTATCTTTTTCRTTTTCGT
locus_0010785 GAAATGAATATGTCTTTGTTCTTCTCCATGGTTTGCTCATGAWTCATCTC[A/G]TTCTCACTCACTCACTCGCACACGCACACAAGRTGTTTGCTCYGTGTTAG
locus_0014827 GCAAGCTAAATAATTCTTTTAGGCAAACAAGTTTTGGTGTTCCTCCGCGC[A/G]GAGGGCCAAAGYGAGAGCGCGAGGCGAATAATTMTTGCAAATCACAAGAA
A variety of options are designed to filter based on criteria for a particular project in Sweden. The code is documented sufficiently that it should be possible to apply other custom criteria.
Input files are given with these options. The --dir option can be used alone.
--dir DIR directory containing batch_1.{catalog.{snps,tags}.tsv.gz,sumstats.tsv} files
--snps FILE .snps.tsv.gz file
--tags FILE .tags.tsv.gz file
--sumstats FILE .sumstats.tsv file
To be considered, stack consensus sequences must pass these basic criteria:
--minflank INT minimum flank length; central SNPs are those between flanks [50]
--maxflanksnps INT maximum number of SNPs in each flank [3]
--centralsnpgap INT minimum gap (bp) between central SNPs [5]
Only central SNPs that pass simple filtering according to the following criteria are considered:
--crit_n_region INT min number of regions stack must be scored in [2]
--crit_nwithq INT min number of populations with the minor allele [1]
--crit_qfreq FLOAT min minor allele frequency across all scored populations [0.01]
For all SNP minor alleles, binomial confints are calculated as well:
--alpha FLOAT alpha for minor allele frequency confint (Wilson's method) [0.05]
All central SNPs that are considered are then ranked using these criteria, in order:
Highest number of populations with minor allele across all regions
Highest number of regions with minor allele
Highest number of regions stack was scored in
Highest lower bound of minor allele frequency confint across all regions
Highest minor allele frequency across all regions
The central SNP that is ranked most highly is used, and the others are shifted to the flanks.
These options control output.
--name STRING name prefix for templates, only one of --name or --extended allowed
--extended STRING use extended template names, with STRING for the nonvariable prefix
Extended names are particular to this study.
STRINGR#cP##p###_locusnumber0padded
STRING: the prefix
R#c : the regions containing the minor allele
R3A : all regions
R1N : only north
R1T : only other
R1L : only oland
R2X : north and other
R2Y : north and oland
R2Z : other and oland
P## : Total number of populations with minor allele, 0-padded
p### : Number north, other, oland populations containing minor allele
--padding INT 0-padded with for number suffix on template name [7]
--trimtemplate trim templates to have minflank+SNP+minflank bases [1]
--annotatetemplate add annotation columns to template output, for filtering [1]
--freqdigits INT digits right of decimal point for allele frequences [4]
--D_limit INT only read this number of templates; for debugging
--verbose verbose debugging output