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Old 07-05-2011, 04:00 AM   #1
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Default ChIP-Seq: Tissue-specific prediction of directly regulated genes.

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Tissue-specific prediction of directly regulated genes.

Bioinformatics. 2011 Jun 30;

Authors: McLeay RC, Leat CJ, Bailey TL

Direct binding by a transcription factor (TF) to the proximal promoter of a gene is strong evidence that the TF regulates the gene. Assaying the genome-wide binding of every TF in every cell type and condition is currently impractical. Histone modifications correlate with tissue/cell/condition-specific ("tissue-specific") TF binding, so histone ChIP-seq data can be combined with traditional position-weight matrix (PWM) methods to make tissue-specific predictions of TF-promoter interactions. RESULTS: We use supervised learning to train a na´ve Bayes predictor of TF-promoter binding. The predictor's features are the histone modification levels and a PWM-based score for the promoter. Training and testing uses sets of promoters labeled using TF ChIP-seq data, and we use cross-validation on 23 such datasets to measure accuracy. A PWM+histone na´ve Bayes predictor using a single histone modification (H3K4me3) is substantially more accurate than a PWM score or a conservation-based score (phylogenetic motif model). The na´ve Bayes predictor is more accurate (on average) at all sensitivity levels, and makes only half as many false positive predictions at sensitivity levels from 10% to 80%. On average, it correctly predicts 80% of bound promoters at a false positive rate of 20%. Accuracy does not diminish when we test the predictor in a different cell type (and species) from training. Accuracy is barely diminished even when we train the predictor without using TF ChIP-seq data. AVAILABILITY: Our tissue-specific predictor of promoters bound by a TF is called Dr Gene and is available at http://bioinformatics.org.au/drgene. CONTACT: t.bailey@imb.uq.edu.au.

PMID: 21724591 [PubMed - as supplied by publisher]



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