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|Title:||CENTDIST: Discovery of co-associated factors by motif distribution|
|Source:||Zhang, Z., Chang, C.W., Goh, W.L., Sung, W.-K., Cheung, E. (2011). CENTDIST: Discovery of co-associated factors by motif distribution. Nucleic Acids Research 39 (SUPPL. 2) : W391-W399. ScholarBank@NUS Repository. https://doi.org/10.1093/nar/gkr387|
|Abstract:||Transcription factors (TFs) do not function alone but work together with other TFs (called co-TFs) in a combinatorial fashion to precisely control the transcription of target genes. Mining co-TFs is thus important to understand the mechanism of transcriptional regulation. Although existing methods can identify co-TFs, their accuracy depends heavily on the chosen background model and other parameters such as the enrichment window size and the PWM score cut-off. In this study, we have developed a novel web-based co-motif scanning program called CENTDIST (http://compbio.ddns.comp.nus.edu.sg/∼chipseq/centdist/). In comparison to current co-motif scanning programs, CENTDIST does not require the input of any user-specific parameters and background information. Instead, CENTDIST automatically determines the best set of parameters and ranks co-TF motifs based on their distribution around ChIP-seq peaks. We tested CENTDIST on 14 ChIP-seq data sets and found CENTDIST is more accurate than existing methods. In particular, we applied CENTDIST on an Androgen Receptor (AR) ChIP-seq data set from a prostate cancer cell line and correctly predicted all known co-TFs (eight TFs) of AR in the top 20 hits as well as discovering AP4 as a novel co-TF of AR (which was missed by existing methods). Taken together, CENTDIST, which exploits the imbalanced nature of co-TF binding, is a user-friendly, parameter-less and powerful predictive web-based program for understanding the mechanism of transcriptional co-regulation. © 2011 The Author(s).|
|Source Title:||Nucleic Acids Research|
|Appears in Collections:||Staff Publications|
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