ExploSig Data

Helpers for processing mutation data into standard formats originally developed for the ExploSig family of tools.

• Documentation

Installation

pip install explosig-data

Example

With raw SSM/MAF file from ICGC or TCGA:

>>>importexplosig_dataased>>># Step 1: Process into the ExploSig "standard format":>>>data_container=ed.standardize_ICGC_ssm_file('path/to/ssm.tsv') # if ICGC>>>data_container=ed.standardize_TCGA_maf_file('path/to/maf.tsv') # if TCGA>>># Step 2: Process further>>>data_container.extend_df().to_counts_df('SBS_96', ed.categories.SBS_96_category_list())
>>># Step 3: Access any processed dataframe of interest:>>>ssm_df=data_container.ssm_df>>>extended_df=data_container.extended_df>>>counts_df=data_container.counts_dfs['SBS_96']
>>># Alternatively, use without the chaining API:>>>ssm_df=ed.standardize_ICGC_ssm_file('path/to/ssm.tsv', wrap=False) # if ICGC>>>ssm_df=ed.standardize_TCGA_maf_file('path/to/maf.tsv', wrap=False) # if TCGA>>>extended_df=ed.extend_ssm_df(ssm_df)
>>>counts_df=ed.counts_from_extended_ssm_df(
extended_df, category_colname='SBS_96', category_values=ed.categories.SBS_96_category_list()
)

With data already in the ExploSig "standard format":

>>>importexplosig_dataased>>>importpandasaspd>>># Step 0: Load the data into a dataframe, for example by reading from a TSV file.>>>ssm_df=pd.read_csv('path/to/standard.tsv', sep='\t')
>>># Step 1: Wrap the dataframe using the container class to allow use of the chainable functions.>>>data_container=ed.SimpleSomaticMutationContainer(ssm_df)
>>># Now see step 2 above (or the alternative steps above).

Development

Install for development (in editable mode):

pip install -e .

Build and push to PyPI:

python setup.py sdist bdist_wheel
python -m twine upload dist/*