Python module with various submodules tailored to specific tools, analyses, etc. that I perform across projects. Documentation below is only an introduction, most functions are documented with docstrings.

• Biopython
• HTSeq
• numpy
• pandas
• pybedtools
• pysam (v0.6 or greater)
• PyVCF
• py.test for testing
• seaborn

All of these are available through conda (though you may need the bioconda channel):

conda install biopython htseq numpy pandas pybedtools pysam pyvcf seaborn

Methods for working with bed files. I make heavy use of pybedtools.

This submodule has some methods that are useful for dealing with the output from the RNA-seq expression estimation tool eXpress.

• combine_express_output: Combine multiple eXpress output files into a single pandas dataframe. You can choose which column to combine. You can also aggregate values by gene ID (eXpress estimates transcript expression) if you provide a mapping from transcript IDs to gene IDs. See gencode.make_transcript_gene_se.

Functions for parsing the Gencode gene annotation into various files that are easier to work with.

• make_transcript_gene_se: Make a file with a simple mapping from transcript IDs to gene IDs.
• make_gene_info_df: Make a file indexed by gene ID that has some simple information about each gene.
• make_splice_junction_df: Make a file indexed by splice site that has information about each splice site such as gene, strand, acceptor, donor, etc.

Some methods that are generally useful.

Methods for working with MuTect output.

Provides extended functionality on top of pysam.

• def read_sj_out_tab: Read sj.out.tab file from STAR and parse it.
• def read_external_annotation: Read file with junctions from some database. This does not have to be the same splice junction database used with STAR. The file must have some specific columns (see docstring). Compatible with output from the gencode.make_splice_junction_df.
• def combine_sj_out: Combine SJ.out.tab files from STAR by filtering based on coverage and comparing to an external annotation to discover novel junctions.
• def make_logs_df: Make pandas DataFrame from multiple STAR Log.final.out files.

Useful for tools for working with DNA variants.