Schematic description of the processing steps involved in motif discovery with MotifHound.

<p>(1) Given a set of protein sequences, (2) we enumerate all possible n-mers or motifs (3≤n≤12) present in this query dataset, (3) we then enumerate all degenerate forms of each motif, and we discard those present in less than 3 sequences of the query set. (4) All the motifs retained are counted in the proteome used as background. Note that query sequences are necessarily part of the proteome and are colored in red. (5) The statistics of each motif are k: number of occurrences in the query, l: number of occurrences in the proteome, p: number of sequences in the query, b: number of sequences in the proteome. These are written in a tabulated file used to evaluate the overrepresentation of each motif (6). The <i>P-value</i> reflecting the overrepresentation in the query set relative to the background is calculated by the cumulative hypergeometric distribution (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0106081#s2" target="_blank">material and methods</a>).