FindPeaks 3.1: a tool for identifying areas of enrichment from massively parallel short-read sequencing technology. Summary: Next-generation sequencing can provide insight into protein–DNA association events on a genome-wide scale, and is being applied in an increasing number of applications in genomics and meta-genomics research. However, few software applications are available for interpreting these experiments. We present here an efficient application for use with chromatin-immunoprecipitation (ChIP-Seq) experimental data that includes novel functionality for identifying areas of gene enrichment and transcription factor binding site locations, as well as for estimating DNA fragment size distributions in enriched areas. The FindPeaks application can generate UCSC compatible custom ‘WIG’ track files from aligned-read files for short-read sequencing technology. The software application can be executed on any platform capable of running a Java Runtime Environment. Memory requirements are proportional to the number of sequencing reads analyzed; typically 4 GB permits processing of up to 40 million reads. Availability: The FindPeaks 3.1 package and manual, containing algorithm descriptions, usage instructions and examples, are available at Source files for FindPeaks 3.1 are available for academic use.

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References in zbMATH (referenced in 7 articles )

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  1. Schwartzman, Armin; Jaffe, Andrew; Gavrilov, Yulia; Meyer, Clifford A.: Multiple testing of local maxima for detection of peaks in ChIP-Seq data (2013)
  2. Ding, Min; Wang, Haiyun; Chen, Jiajia; Shen, Bairong; Xu, Zhonghua: Identification and functional annotation of genome-wide ER-regulated genes in breast cancer based on ChIP-Seq data (2012)
  3. Rodríguez-Ezpeleta, Naiara (ed.); Hackenberg, Michael (ed.); Aransay, Ana M. (ed.): Bioinformatics for high throughput sequencing (2012)
  4. Zhu, Lihua J.; Gazin, Claude; Lawson, Nathan D.; Pagès, Hervé; Lin, Simon M.; Lapointe, David S.; Green, Michael R.: Chippeakanno: a bioconductor package to annotate chip-seq and chip-chip data (2010) ioport
  5. Spyrou, Christiana; Stark, Rory; Lynch, Andy G.; Tavaré, Simon: Bayespeak: Bayesian analysis of chip-seq data (2009) ioport
  6. Sun, Wei; Buck, Michael J.; Patel, Mukund; Davis, Ian J.: Improved chip-chip analysis by a mixture model approach (2009) ioport
  7. Fejes, Anthony P.; Robertson, Gordon; Bilenky, Mikhail; Varhol, Richard; Bainbridge, Matthew N.; Jones, Steven J. M.: Findpeaks 3.1: a tool for identifying areas of enrichment from massively parallel short-read sequencing technology. (2008) ioport