FIMO: scanning for occurrences of a given motif

CE Grant, TL Bailey, WS Noble - Bioinformatics, 2011 - academic.oup.com
Bioinformatics, 2011academic.oup.com
A motif is a short DNA or protein sequence that contributes to the biological function of the
sequence in which it resides. Over the past several decades, many computational methods
have been described for identifying, characterizing and searching with sequence motifs.
Critical to nearly any motif-based sequence analysis pipeline is the ability to scan a
sequence database for occurrences of a given motif described by a position-specific
frequency matrix. Results: We describe Find Individual Motif Occurrences (FIMO), a software …
Abstract
Summary: A motif is a short DNA or protein sequence that contributes to the biological function of the sequence in which it resides. Over the past several decades, many computational methods have been described for identifying, characterizing and searching with sequence motifs. Critical to nearly any motif-based sequence analysis pipeline is the ability to scan a sequence database for occurrences of a given motif described by a position-specific frequency matrix.
Results: We describe Find Individual Motif Occurrences (FIMO), a software tool for scanning DNA or protein sequences with motifs described as position-specific scoring matrices. The program computes a log-likelihood ratio score for each position in a given sequence database, uses established dynamic programming methods to convert this score to a P-value and then applies false discovery rate analysis to estimate a q-value for each position in the given sequence. FIMO provides output in a variety of formats, including HTML, XML and several Santa Cruz Genome Browser formats. The program is efficient, allowing for the scanning of DNA sequences at a rate of 3.5 Mb/s on a single CPU.
Availability and Implementation: FIMO is part of the MEME Suite software toolkit. A web server and source code are available at http://meme.sdsc.edu.
Contact:  t.bailey@imb.uq.edu.au; t.bailey@imb.uq.edu.au
Supplementary information:  Supplementary data are available at Bioinformatics online.
Oxford University Press