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SigWinR; the SigWin-detector updated and ported to R
BACKGROUND: Our SigWin-detector discovers significantly enriched windows of (genomic) elements in any sequence of values (genes or other genomic elements in a DNA sequence) in a fast and reproducible way. However, since it is grid based, only (life) scientists with access to the grid can use this to...
Autores principales: | , , , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2009
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2762987/ https://www.ncbi.nlm.nih.gov/pubmed/19807919 http://dx.doi.org/10.1186/1756-0500-2-205 |
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author | de Leeuw, Wim C Rauwerda, Han Inda, Márcia A Bruning, Oskar Breit, Timo M |
author_facet | de Leeuw, Wim C Rauwerda, Han Inda, Márcia A Bruning, Oskar Breit, Timo M |
author_sort | de Leeuw, Wim C |
collection | PubMed |
description | BACKGROUND: Our SigWin-detector discovers significantly enriched windows of (genomic) elements in any sequence of values (genes or other genomic elements in a DNA sequence) in a fast and reproducible way. However, since it is grid based, only (life) scientists with access to the grid can use this tool. Therefore and on request, we have developed the SigWinR package which makes the SigWin-detector available to a much wider audience. At the same time, we have introduced several improvements to its algorithm as well as its functionality, based on the feedback of SigWin-detector end users. FINDINGS: To allow usage of the SigWin-detector on a desktop computer, we have rewritten it as a package for R: SigWinR. R is a free and widely used multi platform software environment for statistical computing and graphics. The package can be installed and used on all platforms for which R is available. The improvements involve: a visualization of the input-sequence values supporting the interpretation of Ridgeograms; a visualization allowing for an easy interpretation of enriched or depleted regions in the sequence using windows of pre-defined size; an option that allows the analysis of circular sequences, which results in rectangular Ridgeograms; an application to identify regions of co-altered gene expression (ROCAGEs) with a real-life biological use-case; adaptation of the algorithm to allow analysis of non-regularly sampled data using a constant window size in physical space without resampling the data. To achieve this, support for analysis of windows with an even number of elements was added. CONCLUSION: By porting the SigWin-detector as an R package, SigWinR, improving its algorithm and functionality combined with adequate performance, we have made SigWin-detector more useful as well as more easily accessible to scientists without a grid infrastructure. |
format | Text |
id | pubmed-2762987 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-27629872009-10-17 SigWinR; the SigWin-detector updated and ported to R de Leeuw, Wim C Rauwerda, Han Inda, Márcia A Bruning, Oskar Breit, Timo M BMC Res Notes Technical Note BACKGROUND: Our SigWin-detector discovers significantly enriched windows of (genomic) elements in any sequence of values (genes or other genomic elements in a DNA sequence) in a fast and reproducible way. However, since it is grid based, only (life) scientists with access to the grid can use this tool. Therefore and on request, we have developed the SigWinR package which makes the SigWin-detector available to a much wider audience. At the same time, we have introduced several improvements to its algorithm as well as its functionality, based on the feedback of SigWin-detector end users. FINDINGS: To allow usage of the SigWin-detector on a desktop computer, we have rewritten it as a package for R: SigWinR. R is a free and widely used multi platform software environment for statistical computing and graphics. The package can be installed and used on all platforms for which R is available. The improvements involve: a visualization of the input-sequence values supporting the interpretation of Ridgeograms; a visualization allowing for an easy interpretation of enriched or depleted regions in the sequence using windows of pre-defined size; an option that allows the analysis of circular sequences, which results in rectangular Ridgeograms; an application to identify regions of co-altered gene expression (ROCAGEs) with a real-life biological use-case; adaptation of the algorithm to allow analysis of non-regularly sampled data using a constant window size in physical space without resampling the data. To achieve this, support for analysis of windows with an even number of elements was added. CONCLUSION: By porting the SigWin-detector as an R package, SigWinR, improving its algorithm and functionality combined with adequate performance, we have made SigWin-detector more useful as well as more easily accessible to scientists without a grid infrastructure. BioMed Central 2009-10-06 /pmc/articles/PMC2762987/ /pubmed/19807919 http://dx.doi.org/10.1186/1756-0500-2-205 Text en Copyright © 2009 Breit et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Technical Note de Leeuw, Wim C Rauwerda, Han Inda, Márcia A Bruning, Oskar Breit, Timo M SigWinR; the SigWin-detector updated and ported to R |
title | SigWinR; the SigWin-detector updated and ported to R |
title_full | SigWinR; the SigWin-detector updated and ported to R |
title_fullStr | SigWinR; the SigWin-detector updated and ported to R |
title_full_unstemmed | SigWinR; the SigWin-detector updated and ported to R |
title_short | SigWinR; the SigWin-detector updated and ported to R |
title_sort | sigwinr; the sigwin-detector updated and ported to r |
topic | Technical Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2762987/ https://www.ncbi.nlm.nih.gov/pubmed/19807919 http://dx.doi.org/10.1186/1756-0500-2-205 |
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