Towards a theoretical understanding of false positives in DNA motif finding.

ABSTRACT:

Background

Detection of false-positive motifs is one of the main causes of low performance in de novo DNA motif-finding methods. Despite the substantial algorithm development effort in this area, recent comprehensive benchmark studies revealed that the performance of DNA motif-finders leaves room for improvement in realistic scenarios.

Results

Using large-deviations theory, we derive a remarkably simple relationship that describes the dependence of false positives on dataset size for the one-occurrence per sequence motif-finding problem. As expected, we predict that false-positives can be reduced by decreasing the sequence length or by adding more sequences to the dataset. Interestingly, we find that the false-positive strength depends more strongly on the number of sequence

SUBMITTER: Zia A 

PROVIDER: S-EPMC3436861 | biostudies-literature | 2012 Jun

REPOSITORIES: biostudies-literature