coVar is a tool for detecting physically-linked mutations in genomic data. Given a sorted, indexed BAM file, reference genome and gene annotation, coVar identifies and counts sequencing reads with unique physically linked mutations.
Currently, to install coVar, you need to have cargo installed.
cargo install covar
covar --version
git clone https://github.com/andersen-lab/covar.git
cd covar
cargo install --path .
covar --version
covar --input <INPUT_BAM> --reference <REFERENCE_FASTA> --annotation <ANNOTATION_GFF>
Flag | Description |
---|---|
-i , --input <INPUT_BAM> |
Input BAM file (must be primer trimmed, sorted, and indexed). |
-r , --reference <REFERENCE_FASTA> |
Reference genome in FASTA format. |
-a , --annotation <ANNOTATION_GFF> |
Annotation GFF3 file for translating nucleotide to amino acid mutations. |
Flag | Default | Description |
---|---|---|
-o , --output <OUTPUT> |
stdout | Output file path. If not provided, results will be printed to stdout. |
-s , --start_site <START> |
0 |
Genomic start position for variant calling. |
-e , --end_site <END> |
reference length | Genomic end position for variant calling. Defaults to the length of the reference genome. |
-d , --min_depth <DEPTH> |
1 |
Minimum coverage depth for a mutation cluster to be considered. |
-f , --min_frequency <FREQ> |
0.001 |
Minimum mutation frequency (cluster depth / total depth). |
-q , --min_quality <QUAL> |
20 |
Minimum base quality score for variant calling. |
-t , --threads <THREADS> |
1 |
Number of threads to use for processing. |
covar \
-i sample.bam \
-r reference.fasta \
-a annotation.gff3
covar \
-i sample.bam \
-r reference.fasta \
-a annotation.gff3 \
-s 1000 \
-e 5000 \
-o output.tsv
covar \
-i sample.bam \
-r reference.fasta \
-a annotation.gff3 \
-d 5 \
-q 30 \
-f 0.01 \
-t 4
The output is a tab-delimited file (.tsv) with the following columns:
Column | Description |
---|---|
nt_mutations |
Nucleotide mutations for this cluster |
aa_mutations |
Corresponding amino acid translations (where possible*) |
cluster_depth |
Total number of read pairs with this cluster of mutations |
total_depth |
Total number of reads spanning this cluster |
frequency |
Mutation frequency (cluster depth / total depth) |
coverage_start |
Maximum read start site for which this cluster was detected |
coverage_end |
Minimum read end site for which this cluster was detected |
*Note: Not all nucleotide mutations will have a corresponding amino acid mutations. For example, SNPs in codons that span reads or frameshift indels will be translated as 'Unknown' and 'NA', respectively.