cstag 0.6.2

Python module to manipulate the minimap2's CS tag

cstag

cstag is a Python library tailored for the manipulation and handling of minimap2's CS tags.

🌟 Features

• cstag.call(): Generate a CS tag
• cstag.shorten(): Convert a CS tag from its long to short format
• cstag.lengthen(): Convert a CS tag from its short to long format
• cstag.consensus(): Create a consensus CS tag from multiple CS tags
• cstag.mask(): Mask low-quality bases within a CS tag
• cstag.split(): Break down a CS tag into its constituent parts
• cstag.revcomp(): Convert a CS tag to its reverse complement
• cstag.to_sequence(): Reconstruct a reference subsequence from the alignment
• cstag.to_vcf(): Generate a VCF file
• cstag.to_html(): Produce an HTML representation

For comprehensive documentation, please visit our docs.
To add CS tags to SAM/BAM files, check out cstag-cli.

🛠 Installation

Using PyPI:

pip install cstag

Using Bioconda:

conda install -c bioconda cstag

💡 Usage

Generating CS Tags

import cstag

cigar = "8M2D4M2I3N1M"
md = "2A5^AG7"
seq = "ACGTACGTACGTACG"

print(cstag.call(cigar, md, seq))
# :2*ag:5-ag:4+ac~nn3nn:1

cstag.call(cigar, md, seq, long=True)
# =AC*ag=TACGT-ag=ACGT+ac~nn3nn=G

Shortening or Lengthening CS Tags

import cstag

# Convert a CS tag from long to short
cs_tag = "=ACGT*ag=CGT"

cstag.shorten(cs_tag)
# :4*ag:3


# Convert a CS tag from short to long
cs_tag = ":4*ag:3"
cigar = "8M"
seq = "ACGTACGT"

cstag.lengthen(cs_tag, cigar, seq)
# =ACGT*ag=CGT

Creating a Consensus

import cstag

cs_tags = ["=ACGT", "=AC*gt=T", "=C*gt=T", "=C*gt=T", "=ACT+ccc=T"]
positions = [1, 1, 2, 2, 1]

cstag.consensus(cs_tags, positions)
# =AC*gt*T

Masking Low-Quality Bases

import cstag

cs_tag = "=ACGT*ac+gg-cc=T"
cigar = "5M2I2D1M"
qual = "AA!!!!AA"
phred_threshold = 10
cstag.mask(cs_tag, cigar, qual, phred_threshold)
# =ACNN*an+ng-cc=T

Splitting a CS Tag

import cstag

cs_tag = "=ACGT*ac+gg-cc=T"
cstag.split(cs_tag)
# ['=ACGT', '*ac', '+gg', '-cc', '=T']

Reverse Complement of a CS Tag

import cstag

cs_tag = "=ACGT*ac+gg-cc=T"
cstag.revcomp(cs_tag)
# =A-gg+cc*tg=ACGT

Reconstructing the Reference Subsequence

import cstag
cs_tag = "=AC*gt=T-gg=C+tt=A"
cstag.to_sequence(cs_tag)
# ACTTCTTA

Generating a VCF Report

import cstag
cs_tag = "=AC*gt=T-gg=C+tt=A"
chrom = "chr1"
pos = 1
print(cstag.to_vcf(cs_tag, chrom, pos))
"""
##fileformat=VCFv4.2
#CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO
chr1	3	.	G	T	.	.	.
chr1	4	.	TGG	T	.	.	.
chr1	5	.	C	CTT	.	.	.
"""

The multiple CS tags enable reporting of the variant allele frequency (VAF).

import cstag
cs_tags = ["=ACGT", "=AC*gt=T", "=C*gt=T", "=ACGT", "=AC*gt=T"]
chroms = ["chr1", "chr1", "chr1", "chr2", "chr2"]
positions = [2, 2, 3, 10, 100]
print(cstag.to_vcf(cs_tags, chroms, positions))
"""
##fileformat=VCFv4.2
##INFO=<ID=DP,Number=1,Type=Integer,Description="Total Depth">
##INFO=<ID=RD,Number=1,Type=Integer,Description="Depth of Ref allele">
##INFO=<ID=AD,Number=1,Type=Integer,Description="Depth of Alt allele">
##INFO=<ID=VAF,Number=1,Type=Float,Description="Variant allele frequency (AD/DP)">
#CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO
chr1	4	.	G	T	.	.	DP=3;RD=1;AD=2;VAF=0.667
chr2	102	.	G	T	.	.	DP=1;RD=0;AD=1;VAF=1.0
"""

Generating an HTML Report

import cstag
from pathlib import Path

cs_tag = "=AC+ggg=T-acgt*at~gt10ag=GNNN"
description = "Example"

cs_tag_html = cstag.to_html(cs_tag, description)
Path("report.html").write_text(cs_tag_html)
# Output "report.html"

You can visualize mutations indicated by the CS tag using the generated report.html file as shown below:

📣 Feedback and Support

For questions, bug reports, or other forms of feedback, we'd love to hear from you!
Please use GitHub Issues for all reporting purposes.