alcov 0.1.1

Identify frequencies of concerning mutations from aligned reads

Alcov

Abundance learning for SARS-CoV-2 variants. The primary purpose of the tool is:

• Estimating abundace of variants of concern from wastewater sequencing data

The tool can also be used for:

• Converting nucleotide and amino acid mutations for SARS-CoV-2 such as those found on https://covariants.org/variants/S.N501
• Determining the frequency of mutations of interest in BAM files
• Plotting the depth for each ARTIC amplicon (https://github.com/artic-network/artic-ncov2019/tree/master/primer\_schemes/nCoV-2019/V3)
• Comparing amplicon GC content with its read depth (as a measure of degredation)

The tool is under active development. If you have questions or issues, please open an issue on GitHub or email me (email in setup.py).

Installing

The latest release can be downloaded from PyPI

pip install alcov

This will install the Python library and the CLI.

To install the development version, clone the repository and run

pip install .

Usage example

Estimating relative abundance of variants of concern:

alcov find_lineages reads.bam

Converting mutation names:

$ alcov nt A23063T
A23063T causes S:N501Y
$ alcov aa S:E484K
G23012A causes S:E484K

Finding mutations in BAM file:

alcov find_mutants reads.bam

Finding mutations in BAM files for multiple samples:

alcov find_mutants samples.txt

Where samples.txt looks like:

reads1.bam	Sample 1 name
reads2.bam	Sample 2 name
...

Running find_mutants will print the number of reads with and without each mutation in each sample and then generate a heatmap showing the frequencies for all samples.

You can also specify a custom mutations file:

alcov find_mutants samples.txt mutations.txt

Where mutations.txt looks like:

S:N501Y
G23012A
...

Getting the read depth for each amplicon

alcov amplicon_coverage reads.bam

or

alcov amplicon_coverage samples.txt

Plotting amplicon GC content against amplicon depth

alcov gc_depth reads.bam

or

alcov gc_depth samples.txt