sequenceTools

A package with tools for processing DNA sequencing data

Version on this page:1.4.0.5
LTS Haskell 22.14:1.5.3.1
Stackage Nightly 2024-03-28:1.5.3.1
Latest on Hackage:1.5.3.1

See all snapshots sequenceTools appears in

GPL-3.0-only licensed by Stephan Schiffels
Maintained by [email protected]
This version can be pinned in stack with:sequenceTools-1.4.0.5@sha256:a431536cf437e5816df7623b4e75e54464cb474fd0fe2e5e2bd8feab7d73b05b,2850

Module documentation for 1.4.0.5

SequenceTools

Anaconda package

(bioconda package available thanks to apeltzer!)

This repository contains some programs that I use for processing sequencing data.

Simple Installation of the main tools

  1. Download stack (https://docs.haskellstack.org/en/stable/README/#how-to-install).
  2. Run stack install sequenceTools --resolver nightly. You should now have the executables from this package under ~/.local/bin.
  3. Add ~/.local/bin to your PATH, for example by adding to your ~/.profile or ~/.bash_profile the line PATH=$PATH:$HOME/.local/bin. Run source ~/.profile or source ~/.bash_profile, respectively, to update your path.
  4. Run pileupCaller --version. It should output 1.4.0. You’re all set.

pileupCaller

The main tool in this repository is the program pileupCaller to sample alleles from low coverage sequence data. The first step is to generate a “pileup” file at all positions you wish to genotype. To do that, here is a typical command line, which restricts to mapping and base quality of 30:

samtools mpileup -R -B -q30 -Q30 -l <list_of_positions.txt> \
    -f <reference_genome.fasta> \
    Sample1.bam Sample2.bam Sample3.bam > pileup.txt

Important Note: You should definitely use the -B flag, which disables base alignment quality recalibration. This mechanism is turned on by default and causes huge reference bias with low coverage ancient DNA data. This flag disables the mechanism.

In the above command line, the file “list_of_positions.txt” should either contain positions (0-based) or a bed file (see samtools manual for details). The output is a simple text file with all positions that could be genotyped in the three samples.

Next, you need to run my tool pileupCaller, which you run like this:

pileupCaller --randomHaploid --sampleNames Sample1,Sample2,Sample3 \
    --samplePopName MyPop -f <Eigenstrat.snp> \
    -e <My_output_prefix> < pileup.txt

Here, options --sampleNames gives the names of the samples that is output in the Eigenstrat *.ind file, and and -–samplePopName is optional to also give the population names in that file (defaults to Unknown, you can also change it later in the output). Then, option -f gives an Eigenstrat positions file. This is important because the pileup file only contains sites which could be called in at least one of your samples. In order to later merge your dataset with another Eigenstrat file, pileupCaller will check every position in the other Eigenstrat file to make sure every position is output with the correct alleles and missing genotypes if appropriate. Finally, the -e option specifies Eigenstrat as output format and gives the prefix for the *.ind, *.pos and *.geno files. Without the -e option, pileupCaller will output in FreqSum format, described here, which is useful for debugging your pipeline, since it’s just a single file that is output into the terminal and can therefore easily be inspected.

You can also get some help by typing pileupCaller -h, which shows a lot more option, for example the sampling method, minimal coverage and other important options.

Note that you can also fuse the two steps above into one unix pipe:

samtools mpileup -R -B -q30 -Q30 -l <list_of_positions.txt> \
    -f <reference_genome.fasta> \
    Sample1.bam Sample2.bam Sample3.bam | \
pileupCaller --randomHaploid --sampleNames Sample1,Sample2,Sample3 \
    --samplePopName MyPop -f <Eigenstrat.snp> \
    -e <My_output_prefix>

There is however an issue here: If you have aligned your read data to a version of the reference genome that uses chr1, chr2 and so on as chromosome names, the resulting Eigenstrat file will be valid, but won’t merge with other Eigenstrat datasets that use chromosome names 1, 2 and so on. I would therefore recommend to strip the chr from your chromosome names if necessary. You can do that easily using a little UNIX filter using the sed tool. In the full pipeline, it looks like this:

samtools mpileup -R -B -q30 -Q30 -l <list_of_positions.txt> \
    -f <reference_genome.fasta> \
    Sample1.bam Sample2.bam Sample3.bam | sed 's/chr//' | \
pileupCaller --sampleNames Sample1,Sample2,Sample3 \
    --samplePopName MyPop -f <Eigenstrat.snp> \
    -o EigenStrat -e <My_output_prefix>

vcf2eigenstrat

Simple tool to convert a VCF file to an Eigenstrat file. Pretty self-explanatory. Please run vcf2eigenstrat --help to output some documentation.

genoStats

A simple tool to get some per-individual statistics from an Eigenstrat or Freqsum-file. Run genoStats --help for documentation.

Scripts

This package also contains several haskell wrapper scripts for the following ADMIXTOOLS and EIGENSOFT commands: convertf, mergeit, qp3Pop, qpDstat and smartPCA. The original tools require parameter files as input, which I find tedious to use in bioinformatics pipelines. I wrote those wrapper scripts to be able to start the tools with a simple command line option interface.

If you have stack installed your system (see above), you should be able to run those scripts on your machine without any difficult setup. Simply clone this repository, navigate to the scripts subfolder and invoke any script using standard bash execution, for example

./convertf_wrapper.hs

If you start this the first time it may take a while, since stack downloads all dependencies and even the script interpreter for you, but after that it should start instantanious. If you want to use the scripts from your path, I suggest to put symbolic links into any folder that is already on your path (for example ~/.local/bin).

Changes

V 1.2.3 : Adapted to newest sequence-formats. Had to change all the chromosome-related code to the newType Chrom datatype. Also started implementing normaliseBimWithVCF.

V 1.2.4: normaliseBimWithVCF is ready.

V 1.3.0: Lots of refactoring. Lots of testing. Removed some features in vcf2eigenstrat and in pileupCaller, including the option in pileupCaller to call without a SNP file.

V 1.3.1: Bumped dependency on sequence-formats to new sequence-formats-1.4.0, which includes strand-information in pileup data, as well as rsIds in freqSum to output the correct rsId, and an option to parse chromosomes X, Y and MT.

V 1.4.0: Added single strand mode, and new triallelic treatment.

V 1.4.0.1: Improved README, fixed output bug in genoStats.hs

V 1.4.0.3: Updated to new sequence-formats version, now including reading of genetic position from eigenstrat files.

V 1.4.0.4:

  • Fixed eigenstrat-output in pileupCaller to add a dot after the outputprefix before the file extensions.
  • Updated haskell-stack wrapper scripts for EIGENSOFT and ADMIXTOOLS.
  • Moved unmaintained scripts into unmaintained folder.