RT Journal Article
SR Electronic
T1 Regmex, Motif analysis in ranked lists of sequences
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 035956
DO 10.1101/035956
A1 Morten Muhlig Nielsen
A1 Paula Tataru
A1 Tobias Madsen
A1 Asger Hobolth
A1 Jakob Skou Pedersen
YR 2016
UL http://biorxiv.org/content/early/2016/01/05/035956.abstract
AB Motif analysis has long been an important method to characterize biological functionality and the current growth of sequencing-based genomics experiments further extends its potential. These diverse experiments often generate sequence lists ranked by some functional property. There is therefore a growing need for motif analysis methods that can exploit this coupled data structure and be tailored for specific biological questions. Here, we present a motif analysis tool, Regmex (REGular expression Motif EXplorer), which offers several methods to identify overrepresented motifs in a ranked list of sequences. Regmex uses regular expressions to define motifs or families of motifs and embedded Markov models to calculate exact probabilities for motif observations in sequences. Motif enrichment is optionally evaluated using random walks, Brownian bridges, or modified rank based statistics. These features make Regmex well suited for a range of biological sequence analysis problems related to motif discovery. We demonstrate different usage scenarios including rank correlation of microRNA binding sites co-occurring with a U-rich motif. The method is available as an R package.