Package: alcov
AlcovAbundance learning for SARS-CoV-2 variants. The primary purpose of the tool is:Estimating abundace of variants of concern from wastewater sequencing dataYou can read more about how Alcov works in the preprint,Alcov: Estimating Variant of Concern Abundance from SARS-CoV-2 Wastewater Sequencing DataThe tool can also be used for:Converting nucleotide and amino acid mutations for SARS-CoV-2 such as those found onhttps://covariants.org/variants/S.N501Determining the frequency of mutations of interest in BAM filesPlotting 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).InstallingThe latest release can be downloaded from PyPIpip install alcovThis will install the Python library and the CLI.To install the development version, clone the repository and runpip install .Usage examplePreprocessingAlcov expects a BAM file of reads aligned to the SARS-CoV-2 reference genome. For an example of how to process Illumina reads, check theprepdirectory for a script named "prep.py" which outlines our current preprocessing pipeline, including the generation of a "samples.txt" file used by alcov "find_lineages" command.Estimating relative abundance of variants of concern:alcov find_lineages reads.bamFinding lineages in BAM files for multiple samples:alcov find_lineages samples.txtWheresamples.txtlooks like:path/to/reads1.bam	Sample 1 name
path/to/reads2.bam	Sample 2 name
...Example usage: To estimate the relative abundance of lineages in a list of samples (samples.txt), while considering only positions with a minimum depth of 10 reads, the following command can be used. This will also save the heatmap as a .png image and the corresponding frequencies as a csv file.alcov find_lineages --min_depth=10 --save_img=True --csv=True samples.txtOptionally specify which VOCs to look for (Note: This will restrict alcov to only consider the lineages specified in this text file. Do not provide this file if you wish alcov to consider all lineages for which it has constellation files.)alcov find_lineages reads.bam lineages.txtWherelineages.txtlooks like:
Note: These lineages must be chosen from the list of lineages that alcov has constellation files for (updated weekly) found in "alcov/alcov/data/constellations/"BA.5-like
BQ.1.1-like
XBB-like
XBB.1.5-like
...Optionally change minimum read depth (default 40)alcov find_lineages --min_depth=5 reads.bamOptionally show how predicted mutation rates agree with observed mutation ratesalcov find_lineages --show_stacked=True reads.bamUse mutations which are found in multiple VOCs (can help for low coverage samples) - This is now the default behaviour.alcov find_lineages --unique=False reads.bamPlotting change in lineage distributions over time for multiple sitesalcov find_lineages --ts samples.txtWheresamples.txtlooks like:reads1.bam	SITE1_2021-09-10
reads2.bam	SITE1_2021-09-12
...
reads3.bam	SITE2_2021-09-10
reads4.bam	SITE2_2021-09-12
...Converting mutation names:$ alcov nt A23063T
A23063T causes S:N501Y
$ alcov aa S:E484K
G23012A causes S:E484KFinding mutations in BAM file:alcov find_mutants reads.bamFinding mutations in BAM files for multiple samples:alcov find_mutants samples.txtWheresamples.txtlooks like:reads1.bam	Sample 1 name
reads2.bam	Sample 2 name
...Runningfind_mutantswill 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.txtWheremutations.txtlooks like:S:N501Y
G23012A
...Getting the read depth for each ampliconalcov amplicon_coverage reads.bamoralcov amplicon_coverage samples.txtPlotting amplicon GC content against amplicon depthalcov gc_depth reads.bamoralcov gc_depth samples.txt