vdbwrair / vartable

VarTable

Usage

Uses bam-readcount and PyVCF to assist manual curation of viral genomes.

$ vartable_report testdata/fullsample.bam.vcf --bam testdata/fullsample.bam \
                --ref testdata/Den1__WestPac__1997.fasta --type base_caller \
                --mindepth 10 --minpercent 1 --out example.tsv

A BAM file is required to get the columns derived from bam-readcount. If you don't provide a BAM file, you'll get limited information derived from the VCF file. , but if it's provided, you also need to provide the appropriate reference file. You may need to sort or index the BAM.

You'll likely see warnings about the mapping quality; the mapping quality is not working currently due to requirements form bam-readcount.

This tool only reports on positions where the input VCF file has identified a variant. If you want information on other positions, use bam-readcount directly.

Protein translation and Synonymous/Non-snynoymous identification are not yet implemented.

Output Info

"Ref Frequency" and "Alt Frequency" are percentage values.

"Codon", "Codon Type" and translation are currently unsupported.

For bam-redcount:

Project home: https://github.com/genome/bam-readcount

base → the base that all reads following in this field contain at the reported position i.e. C

count → the number of reads containing the base

avg_mapping_quality → the mean mapping quality of reads containing the base

avg_basequality → the mean base quality for these reads

avg_se_mapping_quality → mean single ended mapping quality

num_plus_strand → number of reads on the plus/forward strand

num_minus_strand → number of reads on the minus/reverse strand

avg_pos_as_fraction → average position on the read as a fraction (calculated with respect to the length after clipping). This value is normalized to the center of the read (bases occurring strictly at the center of the read have a value of 1, those occurring strictly at the ends should approach a value of 0)

avg_num_mismatches_as_fraction → average number of mismatches on these reads per base

avg_sum_mismatch_qualities → average sum of the base qualities of mismatches in the reads

num_q2_containing_reads → number of reads with q2 runs at the 3’ end

avg_distance_to_q2_start_in_q2_reads → average distance of position (as fraction of unclipped read length) to the start of the q2 run

avg_clipped_length → average clipped read length of reads

avg_distance_to_effective_3p_end → average distance to the 3’ prime end of the read (as fraction of unclipped read length)

Development

Docker

$ docker-compose -f docker-compose.test.yml -p ci build 
$ docker-compose -f docker-compose.test.yml -p ci up

Setup

$ ./install.sh
$ export PATH=$PWD/miniconda/bin/:$PATH 
$ pip install -r test-requirements.txt

Make sure PATH points to miniconda/bin

Test

$ nosetests test/*.py --nocapture  # don't silence stdout

Test functions must start or end with test or they will be ignored by nosetets

Debugging

$ pip install ipdbplugin
$ nosetests test/*.py --ipdb --ipdb-failure --nocapture

vartable's Issues

Unhandled Compound and Simple location operators

testdata/adeno.gb has the order location attribute, which we don't handle explicitly if it's different form join

There are more, and may be covered in the biopython, scikit-bio, and NCBI documentaiton
There may be parsing rules for genbank files. https://github.com/biocore/scikit-bio/blob/master/skbio/io/format/_sequence_feature_vocabulary.py#L202 'join', 'complement', 'order'

Create Primer test cases

Primer Implementation Plan

Given a reference fasta file, a VCF file, a BAM file, and a primer file:

map primers to reference, creating a new “Primer Bam” file
for each “alt” within the VCF file:
Inspect the “Primer Bam” file to check if that alt overlaps a primer. That is, the alt’s position is between the primer’s map start and map end (a.k.a., it’s mapped region)
count reads that have that alt
count reads that don’t have alt
count reads that have that alt and which end within the primer’s mapped region
count reads that have that don’t have the alt and which end within the primer’s mapped region
return the four counts above

@mousepixels does this match our conclusion today?

Docker and CI stuff incomplete

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Feature Translation Tests

@pirekupcode there is an example genbank file in testdata/adeno.gb.

the test file is all set up in test/test_vartable.py, and the types you need are in vartable/types.py. You can ignore the other files for now.

Document Requirements

Which ones

non-primered reads
primered reads supporting consensus
primered reads support non-consensus
Does it match the primer?
Mismatch with consensus?
Multiple segments (flu)?

PCR Error Documentation

As discussed at first meeting

Add Code Coverage

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Data Model