viola.MultiBedpe.classify_manual_svtype

MultiBedpe.classify_manual_svtype(definitions, ls_conditions, ls_names, ls_order=None, exclude_empty_cases=False)

Classify SV records by user-defined criteria. A new INFO table named ‘manual_sv_type’ will be created.

Parameters

• definitions (path_or_buf or str, default None) –

  Path to the file which specifies the definitions of custom SV classification. This argument is disabled when “ls_condition” is not None. If “default” is specified, the simple length-based SV classification will be employed. If “article” is specified, the same definition file which was used in the Viola publication will be reflected. Below is the links to each of definition file you can specify on this method.

  ”default” -> https://github.com/dermasugita/Viola-SV/blob/master/examples/demo_sig/resources/definitions/sv_class_default.txt

  ”article” -> https://github.com/dermasugita/Viola-SV/blob/master/examples/demo_sig/resources/definitions/sv_class_article.txt

• ls_conditions (List[callable] or List[str], default None) – List of definitions of custom SV classification. The data type of the elements in the list can be callable or SV ID (str). callable –> Functions that takes a self and returns a list of SV ID that satisfy the conditions of the SV class to be defined. SV ID –> Lists of SV ID that satisfy the conditions of the SV class to be defined. This argument is disabled when “definitions” is not None.

• ls_names (List[str], default None) – List of the names of the custom SV class corresponding to the “ls_conditions”. This argument is disabled when “definitions” is not None.

• return_series (bool, default True) – Return counts of each custom SV class as a pd.Series.

• exclude_empty_cases (bool, default False) – If True, samples which have no SV record will be excluded.

Return type

pd.DataFrame or None