popins4snake

A modularized version of the program PopIns2 for population-scale detection of non-reference sequence variants.

Popins4snake is a program consisting of several functions. The functions are designed to be chained into a workflow, together with calls to standard bioinformatics programs (samtools, bwa, ...) and bash commands.

The recommended way of running popins4snake is using the Snakemake workflow PopinSnake.

Contents

1. Requirements
2. Installation
3. Usage and Functions
4. References

Requirements

Prior to the installation make sure your system meets all the requirements:

For the default settings of popins4snake a Bifrost installation with MAX_KMER_SIZE=64 is required (see below). Presently, the conda package of Bifrost does not meet this requirement. Therefore, Bifrost is included as a submodule in this repository.

CMake is required for installing Bifrost.

The SeqAn header library is included in this repository and comes with the git clone. There is no need for a manual installation.

Installation

First clone the repository with the --recursive flag:

git clone --recursive https://gitlab.informatik.hu-berlin.de/fonda_a6/popins4snake.git

Next, compile and install Bifrost with MAX_KMER_SIZE=64. You can either install it globally on your system or locally in your home directory. We here describe how to install it locally in a folder external/bifrost/local. This is the location, where the popins4snake Makefile will look for it by default.

cd external/bifrost && mkdir build && cd build
mkdir ../local
cmake .. -DCMAKE_INSTALL_PREFIX=../local -DMAX_KMER_SIZE=64
make
make install

Now, you can compile popins4snake:

cd popins4snake
mkdir build
make

After the compilation with make you should see the binary popins4snake in the cloned directory.

The PopIns2 Wiki gathers known issues that might occur during installation or runtime.

Usage and Functions

The recommended way of running popins4snake is using the Snakemake workflow PopinSnake.

To get an overview of the functions offered in popins4snake, you can run ./popins4snake -h after installation. To display the help page of each of the popins4snake functions, type ./popins4snake <command> --help. The former will print something similar to this:

=====================================================================
A modularized version of the program PopIns2
    for population-scale detection of non-reference sequence variants
=====================================================================

SYNOPSIS
    ./popins4snake COMMAND [OPTIONS]

COMMAND
    crop-unmapped       Extract unmapped and poorly aligned reads from a BAM file.
    merge-bams          Merge two name-sorted BAM files of the same sample and set mate information of now paired reads.
    merge-contigs       Merge sets of contigs into supercontigs using a colored compacted de Bruijn Graph.
    find-locations      Find insertion locations of (super-)contigs per sample.
    merge-locations     Merge insertion locations from all samples into one file.
    place-refalign      Find positions of (super-)contigs by aligning contig ends to the reference genome.
    place-splitalign    Find positions of (super-)contigs by split-read alignment (per sample).
    place-finish        Combine (super-)contig positions found by split-read alignment from all samples.
    genotype            Determine genotypes of all insertions in a sample.

VERSION
    0.1.0-a52d4f5, Date: 2022-08-25 14:42:31

Try `./popins4snake COMMAND --help' for more information on each command.

The crop-unmapped function

popins4snake crop-unmapped [OPTIONS] sample.bam

The crop-unmapped command identifies reads without high-quality alignment to the reference genome. The reads given in the input BAM file must be indexed, i.e. the file sample.bam.bai is expected to exist.

The merge-bams function

popins4snake merge-bams [OPTIONS] input1.bam input2.bam

The merge-contigs function

popins4snake merge-contigs [OPTIONS] {-s|-r} /path/to/sample_directories/

[Default] The merge command builds a colored and compacted de Bruijn Graph (ccdbg) of all contigs of all samples in a given source directory DIR. By default, the merge module finds all files of the pattern <DIR>/*/assembly_final.contigs.fa. To process the contigs of the assemble command the -r input parameter is recommended. Once the ccdbg is built, the merge module identifies paths in the graph and returns supercontigs.

popins4snake merge-contigs [OPTIONS] -y input.gfa -z input.bfg_colors

An alternative way of providing input for the merge command is to directly pass a ccdbg. Here, the merge command expects a GFA file and a bfg_colors file, which is specific to the Bifrost. If you choose to run the merge command with a pre-built GFA graph, mind that you have to set the Algorithm options accordingly (in particular -k).

The find-locations function

popins4snake find-locations [OPTIONS] SAMPLE_ID

The merge-locations function

popins4snake merge-locations [OPTIONS]

The place function

popins4snake place-refalign [OPTIONS]
popins4snake place-splitalign [OPTIONS] SAMPLE_ID
popins4snake place-finish [OPTIONS]

In brief, the place commands attempt to anker the supercontigs to the samples. At first, all potential anker locations from all samples are collected. Then prefixes/suffixes of the supercontigs are aligned to all collected locations. For successful alignments records are written to a VCF file. In the second step, all remaining locations are split-aligned per sample. Finally, all locations from all successful split-alignments are combined and added to the VCF file.

The genotype function

popins4snake genotype [OPTIONS] SAMPLE_ID

The genotype command generates alleles (ALT) of the supercontigs with some flanking reference genome sequence. Then, the reads of a sample are aligned to ALT and the reference genome around the breakpoint (REF). The ratio of alignments to ALT and REF determines a genotype quality and a final genotype prediction per variant per sample.

References

Krannich T., White W. T. J., Niehus S., Holley G., Halldórsson B. V., Kehr B. (2022) Population-scale detection of non-reference sequence variants using colored de Bruijn graphs. Bioinformatics, 38(3):604–611.

Kehr B., Helgadóttir A., Melsted P., Jónsson H., Helgason H., Jónasdóttir Að., Jónasdóttir As., Sigurðsson Á., Gylfason A., Halldórsson G. H., Kristmundsdóttir S., Þorgeirsson G., Ólafsson Í., Holm H., Þorsteinsdóttir U., Sulem P., Helgason A., Guðbjartsson D. F., Halldórsson B. V., Stefánsson K. (2017). Diversity in non-repetitive human sequences not found in the reference genome. Nature Genetics, 49(4):588–593.

Kehr B., Melsted P., Halldórsson B. V. (2016). PopIns: population-scale detection of novel sequence insertions. Bioinformatics, 32(7):961-967.