Bio.motifs.thresholds module
Approximate calculation of appropriate thresholds for motif finding.
- class Bio.motifs.thresholds.ScoreDistribution(motif=None, precision=10**3, pssm=None, background=None)
Bases:
object
Class representing approximate score distribution for a given motif.
Utilizes a dynamic programming approach to calculate the distribution of scores with a predefined precision. Provides a number of methods for calculating thresholds for motif occurrences.
- __init__(motif=None, precision=10**3, pssm=None, background=None)
Initialize the class.
- modify(scores, mo_probs, bg_probs)
Modify motifs and background density.
- threshold_fpr(fpr)
Approximate the log-odds threshold which makes the type I error (false positive rate).
- threshold_fnr(fnr)
Approximate the log-odds threshold which makes the type II error (false negative rate).
- threshold_balanced(rate_proportion=1.0, return_rate=False)
Approximate log-odds threshold making FNR equal to FPR times rate_proportion.
- threshold_patser()
Threshold selection mimicking the behaviour of patser (Hertz, Stormo 1999) software.
It selects such a threshold that the log(fpr)=-ic(M) note: the actual patser software uses natural logarithms instead of log_2, so the numbers are not directly comparable.