isovar 0.2.1

Assemble transcript sequences fragments near variants

isovar

Abundance quantification of distinct transcript sequences containing somatic variants from cancer RNAseq

Example

$ isovar-protein-sequences.py  \
    --vcf somatic-variants.vcf  \
    --bam rnaseq.bam \
    --genome hg19 \
    --min-reads 2 \
    --protein-sequence-length 30 \
    --output isovar-results.csv

  chr       pos ref alt                      amino_acids  \
0  22  46931060   A   C   FGVEAVDHGWPSMSSGSSWRASRGPPPPPR
1  22  46931062   G   A  CFGVEAVDHGWPPMSLAHGGPAVVHRLHPEA

   variant_aa_interval_start  variant_aa_interval_end ends_with_stop_codon  \
0                         16                       17                False
1                         16                       17                False

  frameshift  translations_count  supporting_variant_reads_count  \
0      False                   1                               1
1      False                   1                               1

   total_variant_reads  supporting_transcripts_count  total_transcripts  \
0                  130                             2                  2
1                  127                             2                  2

     gene
0  CELSR1
1  CELSR1

Algorithm/Design

The one line explanation of isovar: ProteinSequence = VariantSequence + ReferenceContext.

A little more detail about the algorithm: 1. Scan through an RNAseq BAM file and extract sequences overlapping a variant locus (represented by ReadAtLocus) 2. Make sure that the read contains the variant allele and split its sequence into prefix/alt/suffix string parts (represented by VariantRead) 3. Combine multiple VariantRead records into a VariantSequence 4. Gather possible reading frames for distinct reference sequences around the variant locus (represented by ReferenceContext). 5. Use the reading frame from a ReferenceContext to translate a VariantSequence into a protein fragment (represented by Translation). 6. Multiple distinct variant sequences and reference contexts can generate the same translations, so we aggregate those equivalent Translation objects into a ProteinSequence.

Since we may not want to deal with every possible translation of every distinct sequence detected around a variant, isovar sorts the variant sequences by the number of supporting reads and the reference contexts in order of protein length and a configurable number of translated protein fragments can be kept from this ordering.