FindPeaks 3.1: A tool for identifying areas of enrichment from massively parallel short-read sequencing technology
dc.contributor.author | Fejes, A. | |
dc.contributor.author | Robertson, G. | |
dc.contributor.author | Bilenky, M. | |
dc.contributor.author | Varhol, Richard | |
dc.contributor.author | Bainbridge, M. | |
dc.contributor.author | Jones, S. | |
dc.date.accessioned | 2017-01-30T10:42:09Z | |
dc.date.available | 2017-01-30T10:42:09Z | |
dc.date.created | 2016-09-12T08:37:05Z | |
dc.date.issued | 2008 | |
dc.identifier.citation | Fejes, A. and Robertson, G. and Bilenky, M. and Varhol, R. and Bainbridge, M. and Jones, S. 2008. FindPeaks 3.1: A tool for identifying areas of enrichment from massively parallel short-read sequencing technology. Bioinformatics. 24 (15): pp. 1729-1730. | |
dc.identifier.uri | http://hdl.handle.net/20.500.11937/4856 | |
dc.identifier.doi | 10.1093/bioinformatics/btn305 | |
dc.description.abstract |
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. © 2008 The Author(s). | |
dc.publisher | Oxford University Press | |
dc.title | FindPeaks 3.1: A tool for identifying areas of enrichment from massively parallel short-read sequencing technology | |
dc.type | Journal Article | |
dcterms.source.volume | 24 | |
dcterms.source.number | 15 | |
dcterms.source.startPage | 1729 | |
dcterms.source.endPage | 1730 | |
dcterms.source.issn | 1367-4803 | |
dcterms.source.title | Bioinformatics | |
curtin.department | Department of Health Policy and Management | |
curtin.accessStatus | Open access via publisher |
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