smallgenomeutilities

The smallgenomeutilities are a collection of scripts that is useful for dealing and manipulating NGS data of small viral genomes. They are written in Python 3 with a small number of dependencies.

The smallgenomeutilities are part of the V-pipe workflow for analysing NGS data of short viral genomes.

Dependencies

You can install these python modules either using pip or bioconda:

• biopython
• bcbio-gff
• numpy
• pandas
• progress
• pysam
• pysamstats
• sklearn
• matplotlib
• progress
• pyyaml

In addition to the modules, frameshift_deletions_checks currently requires mafft being installed -- it is also available on bioconda.

Installation

The recommended way to install the smallgenomeutilities is using the bioconda package:

mamba install smallgenomeutilities

Another possibility is using pip:

# install from the current directory
pip install --editable .

# install from GitHub
pip install git+https://github.com/cbg-ethz/smallgenomeutilities.git

# install from Pypi
pip install smallgenomeutilities

Description of utilities

aln2basecnt

extract base counts and coverage information from a single alignment file

compute_mds

Compute multidimensional scaling for visualizing distances among reconstructed haplotypes.

convert_qr

Convert QuasiRecomb output of a transmitter and recipient set of haplotypes to a combined set of haplotypes, where gaps have been filtered. Optionally translate to peptide sequence.

convert_reference

Perform a genomic liftover. Transform an alignment in SAM or BAM format from one reference sequence to another. Can replace M states by =/X.

coverage

Calculate average coverage for a target region on a different contig.

coverage_stats

Calculate average coverage for a target region of an alignment.

extract_consensus

Build consensus sequences including either the majority base or the ambiguous bases from an alignment (BAM) file.

extract_coverage_intervals

Extract regions with sufficient coverage for running ShoRAH. Half-open intervals are returned, [start:end), and 0-based indexing is used.

extract_sam

Extract subsequences of an alignment, with the option of converting it to peptide sequences. Can filter on the basis of subsequence frequency or gap frequencies in subsequences.

extract_seq

Extract sequences of alignments into a FASTA file where the sequence id matches a given string.

frameshift_deletions_checks

Produce a report about frameshifting indels in a consensus sequences

gather_coverage

gather multiple per sample coverage information into a single unified file

mapper

Determine the genomic offsets on a target contig, given an initial contig and offsets. Can be used to map between reference genomes.

min_coverage

find the minimum coverage in a region from an alignment

minority_freq

Extract frequencies of minority variants from multiple samples. A region of interest is also supported.

pair_sequences

Compare sequences from a multiple sequence alignment from transmitter and recipient samples in order to determine the optimal matching of transmitters to recipients.

predict_num_reads

Predict number of reads after quality preprocessing.

prepare_primers

Starting with a primers BED file, generate the other files used by V-pipe (inserts BED file, and TSV and FASTA file of primers sequences)

remove_gaps_msa

Given a multiple sequence alignment, remove loci with a gap fraction above a certain threshold.

Contributions

• David Seifert <david.seifert@bsse.ethz.ch>
• Susana Posada Cespedes <susana.posada@bsse.ethz.ch>
• Ivan Blagoev Topolsky <ivan.topolsky@sib.swiss>
• Lara Fuhrmann <lara.fuhrmann@bsse.ethz.ch>
• Mateo Carrara <carrara@nexus.ethz.ch>