Metadata-Version: 1.1
Name: topiary
Version: 0.0.6
Summary: Predict cancer epitopes from cancer sequence data
Home-page: https://github.com/hammerlab/topiary
Author: Alex Rubinsteyn, Tavi Nathanson
Author-email: alex {dot} rubinsteyn {at} gmail {dot} com
License: http://www.apache.org/licenses/LICENSE-2.0.html
Description: Topiary
        =======
        
        Predict mutation-derived cancer T-cell epitopes from (1) somatic
        variants (2) tumor RNA expression data, and (3) patient HLA type.
        
        Example
        -------
        
        .. code:: sh
        
            ./topiary \
              --vcf somatic.vcf \
              --mhc-pan \
              --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-file genes.fpkm_tracking \
              --rna-min-gene-expression 4.0 \
              --rna-transcript-fpkm-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. 79) by running:
        
        ::
        
            pyensembl install --release 79
        
        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
        
        Commandline Arguments
        ---------------------
        
        Genomic Variants
        ~~~~~~~~~~~~~~~~
        
        You must specify at least one variant input file:
        
        -  ``--vcf VCF_FILENAME``: Load a
           `VCF <http://www.1000genomes.org/wiki/analysis/variant%20call%20format/vcf-variant-call-format-version-41>`__
           file
        -  ``--maf MAF_FILENAME``: Load a TCGA
           `MAF <https://wiki.nci.nih.gov/display/TCGA/Mutation+Annotation+Format+%28MAF%29+Specification>`__
           file
        
        Output Format
        ~~~~~~~~~~~~~
        
        -  ``--output-csv OUTPUT_CSV_FILENAME``: Path to an output CSV file
        -  ``--output-html OUTPUT_HTML_FILENAME``: Path to an output HTML file
        
        RNA Expression Filtering
        ~~~~~~~~~~~~~~~~~~~~~~~~
        
        Optional flags to use Cufflinks expression estimates for dropping
        epitopes arising from genes or transcripts that are not highly
        expressed.
        
        -  ``--rna-gene-fpkm-file RNA_GENE_FPKM_FILE``: Cufflinks FPKM tracking
           file containing gene expression estimates.
        -  ``--rna-min-gene-expression RNA_MIN_GENE_EXPRESSION``: Minimum FPKM
           for genes
        -  ``--rna-remap-novel-genes-onto-ensembl``: If a novel gene is fully
           contained within a known Ensembl gene, remap its FPKM expression
           value on the Ensembl gene ID.
        -  ``--rna-transcript-fpkm-file RNA_TRANSCRIPT_FPKM_FILE``: Cufflinks
           FPKM tracking file containing transcript expression estimates.
        -  ``--rna-min-transcript-expression RNA_MIN_TRANSCRIPT_EXPRESSION``:
           Minimum FPKM for transcripts
        
        Choose an MHC Binding Predictor
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
        
        You *must* choose an MHC binding predictor using one of the following
        flags:
        
        -  ``--mhc-pan``: Local NetMHCpan
        -  ``--mhc-cons``: Local NetMHCcons
        -  ``--mhc-random``: Random IC50 values
        -  ``--mhc-smm``: Local SMM
        -  ``--mhc-smm-pmbec``: Local SMM-PMBEC
        -  ``--mhc-pan-iedb``: NetMHCpan via the IEDB web API
        -  ``--mhc-cons-iedb``: NetMHCcons via the IEDB web API
        -  ``--mhc-smm-iedb``: SMM via the IEDB web API
        -  ``--mhc-smm-pmbec-iedb``: SMM-PMBEC via the IEDB web API
        
        MHC Alleles
        ~~~~~~~~~~~
        
        You must specify the alleles to perform binding prediction for using one
        of the following flags:
        
        -  ``--mhc-alleles-file MHC_ALLELES_FILE``: Text file containing one
           allele name per line
        -  ``--mhc-alleles MHC_ALLELES``: Comma separated list of allele names,
           e.g. "HLA-A02:01,HLA-B07:02"
        
        Peptide Length
        ~~~~~~~~~~~~~~
        
        -  ``--mhc-epitope-lengths MHC_EPITOPE_LENGTHS``: comma separated list
           of integers specifying which peptide lengths to use for MHC binding
           prediction
        
        Binding Prediction Filtering
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~
        
        -  ``--keep-wildtype-epitopes``: Topiary will normally discard predicted
           epitopes which don't overlap a mutated region of a protein. Use this
           flag to keep all predicted epitopes you must this
        -  ``--ic50-cutoff IC50_CUTOFF``: Drop peptides with predicted IC50 nM
           greater than this value (typical value is 500.0)
        -  ``--percentile-cutoff PERCENTILE_CUTOFF``: Drop peptides with
           percentile rank of their predicted IC50 (among predictions for a
           particular allele) fall below this threshold (lower values are
           stricter filters, typical value is 2.0)
        
        Misc
        ~~~~
        
        -  ``--padding-around-mutation PADDING_AROUND_MUTATION``: Include more
           unmutated residues around the mutation (useful when combined with
           ``--keep-wildtype-epitopes``)
        -  ``--self-filter-directory SELF_FILTER_DIRECTORY``: Directory of files
           named by MHC allele containing a self peptide ligandome (peptides
           which should be excluded from results)
        -  ``--skip-variant-errors``: If a particular mutation causes an
           exception to be raised during annotation, you can skip it using this
           flag.
        
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Environment :: Console
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
