pVACfuse logo


Fusion detection and annotation

pVACfuse expects an annotated bedpe file with fusion information. Fusion detection will be preformed using INTEGRATE with annotations from INTEGRATE-Neo. It should be possible to start with fusions from another caller, convert the output to bedpe format, annotate the bedpe with INTEGRATE-Neo and then feed these candidates into pVACfuse.

  1. Align RNA with Tophat2 (a requirement of INTEGRATE) to obtain accepted_hits.bam and unmapped.bam

  2. (OPTIONAL) Align WGS DNA with BWA aln/sampe (NOT MEM, a requirement of INTEGRATE) to obtain tumor.dna.bam and normal.dna.bam

  3. Produce a gene annotations file with gtfToGenePred

gtfToGenePred -genePredExt -geneNameAsName2 ref.gtf ref.genePred
cut -f 1-10,12 ref.genePred > tmp.txt
echo -e "#GRCh37.ensGene.name\tGRCh37.ensGene.chrom\tGRCh37.ensGene.strand\tGRCh37.ensGene.txStart\tGRCh37.ensGene.txEnd\tGRCh37.ensGene.cdsStart\tGRCh37.ensGene.cdsEnd\tGRCh37.ensGene.exonCount\tGRCh37.ensGene.exonStarts\tGRCh37.ensGene.exonEnds\tGRCh37.ensemblToGeneName.value" > annot.txt
cat tmp.txt >> annot.txt
  1. Run INTEGRATE to obtain fusions.bedpe

Integrate fusion ref.fa annot.txt bwts accepted_hits.bam unmappeds.bam [tumor.dna.bam normal.dna.bam | tumor.dna.bam]
  1. Run INTEGRATE-Neo to obtain annotated fusions bedpe file

integrate-neo.py -t hla.optitype -f fusions.bedpe -r ref.fa -g ref.genePred -k