mavis/pairing/pairing

product_key()

unique id for the product row

def product_key(bpp: BreakpointPair) -> str:

Args

• bpp (BreakpointPair)

Returns

• str

predict_transcriptome_breakpoint()

for a given genomic breakpoint and the target transcript. Predicts the possible transcriptomic breakpoints that would be expected based on the splicing model for abrogated splice sites

def predict_transcriptome_breakpoint(breakpoint: Breakpoint, transcript):

Args

• breakpoint (Breakpoint): the genomic breakpoint
• transcript (PreTranscript): the transcript

Note

see theory - pairing similar events

equivalent()

compares two events by breakpoint position to see if they are equivalent

def equivalent(
    event1: BreakpointPair, event2: BreakpointPair, distances=None, matching_event_type=True
) -> bool:

Args

• event1 (BreakpointPair)
• event2 (BreakpointPair)
• distances
• matching_event_type

Returns

• bool

pair_by_distance()

for a set of input calls, pair by distance

def pair_by_distance(
    calls: List[BreakpointPair], distances, against_self: bool = False
) -> Dict[str, Set[str]]:

Args

• calls (List[BreakpointPair])
• distances
• against_self (bool)

Returns

• Dict[str, Set[str]]

inferred_equivalent()

comparison of events using product prediction and breakpoint prediction

def inferred_equivalent(
    event1: BreakpointPair, event2: BreakpointPair, reference_transcripts: Dict, distances=None
) -> bool:

Args

• event1 (BreakpointPair)
• event2 (BreakpointPair)
• reference_transcripts (Dict)
• distances

Returns

• bool