Source code for tmtk.highdim.CopyNumberVariation

from .HighDimBase import HighDimBase
import tmtk.utils as utils

[docs]class CopyNumberVariation(HighDimBase): """ Base class for copy number variation datatypes (aCGH, qDNAseq) """ @property def samples(self): return [h.rsplit('.', 1)[0] for h in self.header[1:]] @property def allowed_header(self): return ['probhomloss', 'probloss', 'probnorm', 'probgain', 'probamp', 'segmented', 'chip', 'flag', ]
[docs] def remap_to(self, destination=None): """ :param destination: :return: """ return self._remap_to_chromosomal_regions(destination)
def _validate_probabilities(self): bad_regions = [] bad_samples = [] everything_okay = True for sample in set(self.samples): columns = self.header.str.contains(sample + '.prob') sample_df = self.df.iloc[:, columns].astype(float) sample_df = sample_df.dropna() not_near_1 = ~sample_df.sum(axis=1).between(0.99, 1.01) if any(not_near_1): everything_okay = False bad_samples.append(sample) [bad_regions.append(x) for x in self.df.loc[not_near_1, self.df.columns[0]]] # Adds region ids to list. if not everything_okay: m = 'Samples ({}) where have regions where CNV probabilities do not approximate 1. ' \ 'Regions: {}.'.format(utils.summarise(bad_samples), utils.summarise(bad_regions)) if self.params.get('PROB_IS_NOT_1', 'ERROR') == 'WARN': self.msgs.warning(m) else: self.msgs.error(m) else: self.msgs.okay('All probabilities approximate 1.') def _validate_header_extensions(self): """ Makes checks to determine whether transmart-batch likes this file. Checks whether header contains the <samplecode>.<probability_type>. """ self._check_header_extensions()