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Shape-based peak identification for ChIP-Seq

Shape-based peak identification for ChIP-Seq,10.1186/1471-2105-12-15,BMC Bioinformatics,Valerie Hower,Steven N. Evans,Lior Pachter

Shape-based peak identification for ChIP-Seq   (Citations: 3)
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BACKGROUND: The identification of binding targets for proteins using ChIP-Seq has gained popularity as an alternative to ChIP-chip. Sequencing can, in principle, eliminate artifacts associated with microarrays, and cheap sequencing offers the ability to sequence deeply and obtain a comprehensive survey of binding. A number of algorithms have been developed to call "peaks" representing bound regions from mapped reads. Most current algorithms incorporate multiple heuristics, and despite much work it remains difficult to accurately determine individual peaks corresponding to distinct binding events. RESULTS: Our method for identifying statistically significant peaks from read coverage is inspired by the notion of persistence in topological data analysis and provides a non-parametric approach that is statistically sound and robust to noise in experiments. Specifically, our method reduces the peak calling problem to the study of tree-based statistics derived from the data. We validate our approach using previously published data and show that it can discover previously missed regions. CONCLUSIONS: The difficulty in accurately calling peaks for ChIP-Seq data is partly due to the difficulty in defining peaks, and we demonstrate a novel method that improves on the accuracy of previous methods in resolving peaks. Our introduction of a robust statistical test based on ideas from topological data analysis is also novel. Our methods are implemented in a program called T-PIC (Tree shape Peak Identification for ChIP-Seq) is available at http://bio.math.berkeley.edu/tpic/.
Journal: BMC Bioinformatics , vol. 12, no. 1, pp. 15-9, 2011
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    • ...Comparison with related work Although numerous approaches already exist for the analysis of ChIP-seq data, many of them focus on the peak detection process and provide few or no tools for the interpretation of ChIP-seq peaks [5-8,12-19]...

    Eugenia G Giannopoulouet al. An integrated ChIP-seq analysis platform with customizable workflows

    • ...peak finding programs continue to be developed, among which is a topology­based approach that takes into account the shape of the peaks and uses a tree­based statistic for significance determination [6]...

    Weiqun Penget al. An integrated strategy for identification of both sharp and broad peak...

    • ...Indeed, the shape-based methods presented here have been used to develop a peak-caller– T-PIC–for the ChIP-Seq assay [11]...
    • ...For example, computing test statistics [27] based on the trees constructed from coverage functions and comparing those to the statistics expected from the Galton-Watson trees has been used to determine protein binding sites in ChIP-Seq assay [11]...
    • ...There are also biological applications, for example in the analysis of Chip-Seq experiments [11], as previously mentioned...

    Steven N. Evanset al. Coverage statistics for sequence census methods

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