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mavis.validate.base

class mavis.validate.base.Evidence

inherits BreakpointPair

mavis.validate.base.Evidence.collect_from_outer_window()

determines if evidence should be collected from the outer window (looking for flanking evidence) or should be limited to the inner window (split/spanning/contig only)

def collect_from_outer_window(self):

Returns

  • bool: True or False

mavis.validate.base.Evidence.supporting_reads()

convenience method to return all flanking, split and spanning reads associated with an evidence object

def supporting_reads(self):

mavis.validate.base.Evidence.collect_spanning_read()

spanning read: a read covering BOTH breakpoints

This is only applicable to small events. Do not need to look for soft clipped reads here since they will be collected already

def collect_spanning_read(self, read):

Args

  • read (pysam.AlignedSegment): the putative spanning read

Returns

  • bool: - True: the read was collected and stored in the current evidence object - False: the read was not collected

mavis.validate.base.Evidence.collect_compatible_flanking_pair()

checks if a given read meets the minimum quality criteria to be counted as evidence as stored as support for this event

def collect_compatible_flanking_pair(self, read, mate, compatible_type):

Args

  • read (pysam.AlignedSegment): the read to add
  • mate (pysam.AlignedSegment): the mate
  • compatible_type (SVTYPE): the type we are collecting for

Returns

  • bool: - True: the pair was collected and stored in the current evidence object - False: the pair was not collected

Raises

  • ValueError: if the input reads are not a valid pair

Note

see theory - types of flanking evidence

mavis.validate.base.Evidence.collect_flanking_pair()

checks if a given read meets the minimum quality criteria to be counted as evidence as stored as support for this event

def collect_flanking_pair(self, read, mate):

Args

  • read (pysam.AlignedSegment): the read to add
  • mate (pysam.AlignedSegment): the mate

Returns

  • bool: - True: the pair was collected and stored in the current evidence object - False: the pair was not collected

Raises

mavis.validate.base.Evidence.collect_split_read()

adds a split read if it passes the criteria filters and raises a warning if it does not

def collect_split_read(self, read, first_breakpoint):

Args

  • read (pysam.AlignedSegment): the read to add
  • first_breakpoint (bool): add to the first breakpoint (or second if false)

Returns

  • bool: - True: the read was collected and stored in the current evidence object - False: the read was not collected

Raises

  • NotSpecifiedError: if the breakpoint orientation is not specified

mavis.validate.base.Evidence.decide_sequenced_strand()

given a set of reads, determines the sequenced strand (if possible) and then returns the majority strand found

def decide_sequenced_strand(self, reads):

Args

  • reads

Returns

  • STRAND: the sequenced strand

Raises

  • ValueError: input was an empty set or the ratio was not sufficient to decide on a strand

mavis.validate.base.Evidence.assemble_contig()

uses the split reads and the partners of the half mapped reads to create a contig representing the sequence across the breakpoints

if it is not strand specific then sequences are sorted alphanumerically and only the first of a pair is kept (paired by sequence)

def assemble_contig(self, log=DEVNULL):

Args

  • log

mavis.validate.base.Evidence.load_evidence()

open the associated bam file and read and store the evidence does some preliminary read-quality filtering

def load_evidence(self, log=DEVNULL):

Args

  • log