stacks-integrate-alignments
The stacks-integrate-alignments script will take loci produced by the de novo pipeline,
along with a set of alignments of those loci against a reference genome, and inject the alignment coordinates back into the
de novo-produced data. The program will extract the coordinates of the RAD loci from the given BAM file into a
'locus_coordinates.tsv' table, and it then rewrites the 'catalog.fa.gz'
and 'catalog.calls' files so that they include the genomic coordinates given in
the input BAM file.
These data can be aligned to any reference genome the user is interested in. This may include a closely-realted genome, such as
from the organism itself, to a more distantly related genome. Of course, the more distantly related the genome, the fewer
loci that will be successfully aligned. The user can also filter alignments to exclude poorly mapped loci using several options
including, minimum mapping quality (provided by the alignment program and stored in the BAM file containing the alignments),
minimum alignment coverage and minimum percent identity, both of which are calculated from the CIGAR strings in the supplied
alignments.
Once this integration is complete, we can run the populations program to export, for example,
smoothed FST statistics along the reference genome.
Other Pipeline Programs
Raw reads
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Core
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Execution control
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Utility programs
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The process_radtags program examines raw reads from an Illumina sequencing run and
first, checks that the barcode and the restriction enzyme cutsite are intact (correcting minor errors).
Second, it slides a window down the length of the read and checks the average quality score within the window.
If the score drops below 90% probability of being correct, the read is discarded. Reads that pass quality
thresholds are demultiplexed if barcodes are supplied.
The process_shortreads program performs the same task as process_radtags
for fast cleaning of randomly sheared genomic or transcriptomic data. This program will trim reads that are below the
quality threshold instead of discarding them, making it useful for genomic assembly or other analyses.
The clone_filter program will take a set of reads and reduce them according to PCR
clones. This is done by matching raw sequence or by referencing a set of random oligos that have been included in the sequence.
The kmer_filter program allows paired or single-end reads to be filtered according to the
number or rare or abundant kmers they contain. Useful for both RAD datasets as well as randomly sheared genomic or
transcriptomic data.
The ustacks program will take as input a set of short-read sequences and align them into
exactly-matching stacks. Comparing the stacks it will form a set of loci and detect SNPs at each locus using a
maximum likelihood framework.
A catalog can be built from any set of samples processed
by the ustacks program. It will create a set of consensus loci, merging alleles together. In the case
of a genetic cross, a catalog would be constructed from the parents of the cross to create a set of
all possible alleles expected in the progeny of the cross.
Sets of stacks constructed by the ustacks
program can be searched against a catalog produced by the cstacks program. In the case of a
genetic map, stacks from the progeny would be matched against the catalog to determine which progeny
contain which parental alleles.
The tsv2bam program will transpose data so that it is oriented by locus, instead of by sample.
In additon, if paired-ends are available, the program will pull in the set of paired reads that are associate with each
single-end locus that was assembled de novo.
The gstacks - For de novo analyses, this program will pull in paired-end
reads, if available, assemble the paired-end contig and merge it with the single-end locus, align reads
to the locus, and call SNPs. For reference-aligned analyses, this program will build loci from the
single and paired-end reads that have been aligned and sorted.
This populations program will compute population-level summary statistics such
as π, FIS, and FST. It can output site level SNP calls in VCF format and
can also output SNPs for analysis in STRUCTURE or in Phylip format for phylogenetics analysis.
The denovo_map.pl program executes each of the Stacks components to create a genetic
linkage map, or to identify the alleles in a set of populations.
The ref_map.pl program takes reference-aligned input data and executes each of the Stacks
components, using the reference alignment to form stacks, and identifies alleles. It can be used in a genetic map
of a set of populations.
The load_radtags.pl program takes a set of data produced by either the denovo_map.pl or
ref_map.pl progams (or produced by hand) and loads it into the database. This allows the data to be generated on
one computer, but loaded from another. Or, for a database to be regenerated without re-executing the pipeline.
The stacks-dist-extract script will pull data distributions from the log and distribs
files produced by the Stacks component programs.
The stacks-integrate-alignments script will take loci produced by the de novo pipeline,
align them against a reference genome, and inject the alignment coordinates back into the de novo-produced data.
The stacks-private-alleles script will extract private allele data from the populations program
outputs and output useful summaries and prepare it for plotting.
