The XXmotif web server for eXhaustive, weight matriX-based motif discovery in nucleotide sequences

Gene Center, Department of Biochemistry, and Center for Integrated Protein Science Munich (CIPSM), Ludwig-Maximilians-Universität (LMU) München, Feodor-Lynen-Straße 25, 81377 Munich, Germany.
Nucleic Acids Research (Impact Factor: 9.11). 06/2012; 40(Web Server issue):W104-9. DOI: 10.1093/nar/gks602
Source: PubMed


The discovery of regulatory motifs enriched in sets of DNA or RNA sequences is fundamental to the analysis of a great variety of functional genomics experiments. These motifs usually represent binding sites of proteins or non-coding RNAs, which are best described by position weight matrices (PWMs). We have recently developed XXmotif, a de novo motif discovery method that is able to directly optimize the statistical significance of PWMs. XXmotif can also score conservation and positional clustering of motifs. The XXmotif server provides (i) a list of significantly overrepresented motif PWMs with web logos and E-values; (ii) a graph with color-coded boxes indicating the positions of selected motifs in the input sequences; (iii) a histogram of the overall positional distribution for selected motifs and (iv) a page for each motif with all significant motif occurrences, their P-values for enrichment, conservation and localization, their sequence contexts and coordinates. Free access:

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Article: The XXmotif web server for eXhaustive, weight matriX-based motif discovery in nucleotide sequences

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    • "De novo motif discovery in Ttk69 regions was performed with XXmotif (Luehr et al., 2012) using 200 bp repeat-masked regions centered on the ChIP peak. TOMTOM (Gupta et al., 2007) was used (default parameters, but AT/GC content was set to 0.3/0.2) to match discovered motifs to known Drosophila PWM databases (FlyFactorSurvey, FlyRegv2, idmmpmm2009 and dmmpmm2009) with P-value ≤0.05. "
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    Journal of Cell Science 07/2014; 141(13):2633-43. DOI:10.1242/dev.101956 · 5.43 Impact Factor
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    • "We analyzed DE genes with respect to overrepresented sequence motifs in their promoter regions with the XXmotif tool [39]. Significant motifs were then compared to known position weight matrices (TRANSFAC) of transcription factors (TFs) via STAMP [40]. "
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    • "Then, variants of a predefined IUPAC motif were planted at the top 64 sequences of the dataset. We compared the motifs found by mmHG-Finder to those obtained by using three other methods: the standard MEME program [28], DREME [29], and XXmotif [30]. Selected results of this comparison are summarized in Figure 2, and the full output is shown in Additional file 1. Evidently, mmHG-Finder outperformed all the other three tools on the synthetic examples, which contained degenerate motifs. "
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