openvax / topiary

Predict mutated T-cell epitopes from sequencing data
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Topiary

Predict mutation-derived cancer T-cell epitopes from (1) somatic variants (2) tumor RNA expression data, and (3) patient HLA type.

Example

./topiary \
  --vcf somatic.vcf \
  --mhc-predictor netmhcpan \
  --mhc-alleles HLA-A*02:01,HLA-B*07:02 \
  --ic50-cutoff 500 \
  --percentile-cutoff 2.0 \
  --mhc-epitope-lengths 8-11 \
  --rna-gene-fpkm-tracking-file genes.fpkm_tracking \
  --rna-min-gene-expression 4.0 \
  --rna-transcript-fpkm-tracking-file isoforms.fpkm_tracking \
  --rna-min-transcript-expression 1.5 \
  --output-csv epitopes.csv \
  --output-html epitopes.html

Installation

You can install Topiary and all of the libraries it depends on by running:

pip install topiary

You'll need to download the reference genome sequences and annotations for a recent Ensembl release (e.g. 81) by running:

pyensembl install --release 81 --species human

If you want to work with variants which were aligned against the older reference GRCh37, you will need to also download its annotation data, which is contained in Ensembl release 75:

pyensembl install --release 75 --species human

Commandline Arguments

Genomic Variants

Specify some variants by giving at least one of the following options. They can be used in combination and repeated.

Output Format

RNA Expression Filtering

Optional flags to use Cufflinks expression estimates for dropping epitopes arising from genes or transcripts that are not highly expressed.

Choose an MHC Binding Predictor

You must choose an MHC binding predictor using one of the following values for the --mhc-predictor flag:

MHC Alleles

You must specify the alleles to perform binding prediction for using one of the following flags:

Peptide Length

Binding Prediction Filtering

Misc