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F-Seq: a feature density estimator for high-throughput sequence tags
Summary: Tag sequencing using high-throughput sequencing technologies are now regularly employed to identify specific sequence features, such as transcription factor binding sites (ChIP-seq) or regions of open chromatin (DNase-seq). To intuitively summarize and display individual sequence data as an...
Autores principales: | , , , |
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Formato: | Texto |
Lenguaje: | English |
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Oxford University Press
2008
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2732284/ https://www.ncbi.nlm.nih.gov/pubmed/18784119 http://dx.doi.org/10.1093/bioinformatics/btn480 |
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author | Boyle, Alan P. Guinney, Justin Crawford, Gregory E. Furey, Terrence S. |
author_facet | Boyle, Alan P. Guinney, Justin Crawford, Gregory E. Furey, Terrence S. |
author_sort | Boyle, Alan P. |
collection | PubMed |
description | Summary: Tag sequencing using high-throughput sequencing technologies are now regularly employed to identify specific sequence features, such as transcription factor binding sites (ChIP-seq) or regions of open chromatin (DNase-seq). To intuitively summarize and display individual sequence data as an accurate and interpretable signal, we developed F-Seq, a software package that generates a continuous tag sequence density estimation allowing identification of biologically meaningful sites whose output can be displayed directly in the UCSC Genome Browser. Availability: The software is written in the Java language and is available on all major computing platforms for download at http://www.genome.duke.edu/labs/furey/software/fseq. Contact: terry.furey@duke.edu |
format | Text |
id | pubmed-2732284 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-27322842009-08-27 F-Seq: a feature density estimator for high-throughput sequence tags Boyle, Alan P. Guinney, Justin Crawford, Gregory E. Furey, Terrence S. Bioinformatics Applications Note Summary: Tag sequencing using high-throughput sequencing technologies are now regularly employed to identify specific sequence features, such as transcription factor binding sites (ChIP-seq) or regions of open chromatin (DNase-seq). To intuitively summarize and display individual sequence data as an accurate and interpretable signal, we developed F-Seq, a software package that generates a continuous tag sequence density estimation allowing identification of biologically meaningful sites whose output can be displayed directly in the UCSC Genome Browser. Availability: The software is written in the Java language and is available on all major computing platforms for download at http://www.genome.duke.edu/labs/furey/software/fseq. Contact: terry.furey@duke.edu Oxford University Press 2008-11-01 2008-09-10 /pmc/articles/PMC2732284/ /pubmed/18784119 http://dx.doi.org/10.1093/bioinformatics/btn480 Text en © 2008 The Author(s) http://creativecommons.org/licenses/by-nc/2.0/uk/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Applications Note Boyle, Alan P. Guinney, Justin Crawford, Gregory E. Furey, Terrence S. F-Seq: a feature density estimator for high-throughput sequence tags |
title | F-Seq: a feature density estimator for high-throughput sequence tags |
title_full | F-Seq: a feature density estimator for high-throughput sequence tags |
title_fullStr | F-Seq: a feature density estimator for high-throughput sequence tags |
title_full_unstemmed | F-Seq: a feature density estimator for high-throughput sequence tags |
title_short | F-Seq: a feature density estimator for high-throughput sequence tags |
title_sort | f-seq: a feature density estimator for high-throughput sequence tags |
topic | Applications Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2732284/ https://www.ncbi.nlm.nih.gov/pubmed/18784119 http://dx.doi.org/10.1093/bioinformatics/btn480 |
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