Background: Traditional methods for computational motif discovery often suffer from poor performance. In\r\nparticular, methods that search for sequence matches to known binding motifs tend to predict many\r\nnon-functional binding sites because they fail to take into consideration the biological state of the cell. In recent\r\nyears, genome-wide studies have generated a lot of data that has the potential to improve our ability to identify\r\nfunctional motifs and binding sites, such as information about chromatin accessibility and epigenetic states in\r\ndifferent cell types. However, it is not always trivial to make use of this data in combination with existing motif\r\ndiscovery tools, especially for researchers who are not skilled in bioinformatics programming.\r\nResults: Here we present MotifLab, a general workbench for analysing regulatory sequence regions and\r\ndiscovering transcription factor binding sites and cis-regulatory modules. MotifLab supports comprehensive motif\r\ndiscovery and analysis by allowing users to integrate several popular motif discovery tools as well as different kinds\r\nof additional information, including phylogenetic conservation, epigenetic marks, DNase hypersensitive sites,\r\nChIP-Seq data, positional binding preferences of transcription factors, transcription factor interactions and gene\r\nexpression. MotifLab offers several data-processing operations that can be used to create, manipulate and analyse\r\ndata objects, and complete analysis workflows can be constructed and automatically executed within MotifLab,\r\nincluding graphical presentation of the results.\r\nConclusions: We have developed MotifLab as a flexible workbench for motif analysis in a genomic context. The\r\nflexibility and effectiveness of this workbench has been demonstrated on selected test cases, in particular two\r\npreviously published benchmark data sets for single motifs and modules, and a realistic example of genes\r\nresponding to treatment with forskolin. MotifLab is freely available at http://www.motiflab.org.
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