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BioTile, A Perl based tool for the identification of differentially enriched regions in tiling microarray data
BACKGROUND: Genome-wide tiling array experiments are increasingly used for the analysis of DNA methylation. Because DNA methylation patterns are tissue and cell type specific, the detection of differentially methylated regions (DMRs) with small effect size is a necessary feature of tiling microarray...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3599767/ https://www.ncbi.nlm.nih.gov/pubmed/23452827 http://dx.doi.org/10.1186/1471-2105-14-76 |
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author | Guintivano, Jerry Arad, Michal Tamashiro, Kellie LK Gould, Todd D Kaminsky, Zachary A |
author_facet | Guintivano, Jerry Arad, Michal Tamashiro, Kellie LK Gould, Todd D Kaminsky, Zachary A |
author_sort | Guintivano, Jerry |
collection | PubMed |
description | BACKGROUND: Genome-wide tiling array experiments are increasingly used for the analysis of DNA methylation. Because DNA methylation patterns are tissue and cell type specific, the detection of differentially methylated regions (DMRs) with small effect size is a necessary feature of tiling microarray ‘peak’ finding algorithms, as cellular heterogeneity within a studied tissue may lead to a dilution of the phenotypically relevant effects. Additionally, the ability to detect short length DMRs is necessary as biologically relevant signal may occur in focused regions throughout the genome. RESULTS: We present a free open-source Perl application, Binding Intensity Only Tile array analysis or “BioTile”, for the identification of differentially enriched regions (DERs) in tiling array data. The application of BioTile to non-smoothed data allows for the identification of shorter length and smaller effect-size DERs, while correcting for probe specific variation by inversely weighting on probe variance through a permutation corrected meta-analysis procedure employed at identified regions. BioTile exhibits higher power to identify significant DERs of low effect size and across shorter genomic stretches as compared to other peak finding algorithms, while not sacrificing power to detect longer DERs. CONCLUSION: BioTile represents an easy to use analysis option applicable to multiple microarray platforms, allowing for its integration into the analysis workflow of array data analysis. |
format | Online Article Text |
id | pubmed-3599767 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-35997672013-03-23 BioTile, A Perl based tool for the identification of differentially enriched regions in tiling microarray data Guintivano, Jerry Arad, Michal Tamashiro, Kellie LK Gould, Todd D Kaminsky, Zachary A BMC Bioinformatics Software BACKGROUND: Genome-wide tiling array experiments are increasingly used for the analysis of DNA methylation. Because DNA methylation patterns are tissue and cell type specific, the detection of differentially methylated regions (DMRs) with small effect size is a necessary feature of tiling microarray ‘peak’ finding algorithms, as cellular heterogeneity within a studied tissue may lead to a dilution of the phenotypically relevant effects. Additionally, the ability to detect short length DMRs is necessary as biologically relevant signal may occur in focused regions throughout the genome. RESULTS: We present a free open-source Perl application, Binding Intensity Only Tile array analysis or “BioTile”, for the identification of differentially enriched regions (DERs) in tiling array data. The application of BioTile to non-smoothed data allows for the identification of shorter length and smaller effect-size DERs, while correcting for probe specific variation by inversely weighting on probe variance through a permutation corrected meta-analysis procedure employed at identified regions. BioTile exhibits higher power to identify significant DERs of low effect size and across shorter genomic stretches as compared to other peak finding algorithms, while not sacrificing power to detect longer DERs. CONCLUSION: BioTile represents an easy to use analysis option applicable to multiple microarray platforms, allowing for its integration into the analysis workflow of array data analysis. BioMed Central 2013-03-03 /pmc/articles/PMC3599767/ /pubmed/23452827 http://dx.doi.org/10.1186/1471-2105-14-76 Text en Copyright ©2013 Guintivano 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 | Software Guintivano, Jerry Arad, Michal Tamashiro, Kellie LK Gould, Todd D Kaminsky, Zachary A BioTile, A Perl based tool for the identification of differentially enriched regions in tiling microarray data |
title | BioTile, A Perl based tool for the identification of differentially enriched regions in tiling microarray data |
title_full | BioTile, A Perl based tool for the identification of differentially enriched regions in tiling microarray data |
title_fullStr | BioTile, A Perl based tool for the identification of differentially enriched regions in tiling microarray data |
title_full_unstemmed | BioTile, A Perl based tool for the identification of differentially enriched regions in tiling microarray data |
title_short | BioTile, A Perl based tool for the identification of differentially enriched regions in tiling microarray data |
title_sort | biotile, a perl based tool for the identification of differentially enriched regions in tiling microarray data |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3599767/ https://www.ncbi.nlm.nih.gov/pubmed/23452827 http://dx.doi.org/10.1186/1471-2105-14-76 |
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