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Sandcastle: software for revealing latent information in multiple experimental ChIP-chip datasets via a novel normalisation procedure
ChIP-chip is a microarray based technology for determining the genomic locations of chromatin bound factors of interest, such as proteins. Standard ChIP-chip analyses employ peak detection methodologies to generate lists of genomic binding sites. No previously published method exists to enable compa...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4549617/ https://www.ncbi.nlm.nih.gov/pubmed/26307543 http://dx.doi.org/10.1038/srep13395 |
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author | Bennett, Mark Evans, Katie Ellen Yu, Shirong Teng, Yumin Webster, Richard M. Powell, James Waters, Raymond Reed, Simon H. |
author_facet | Bennett, Mark Evans, Katie Ellen Yu, Shirong Teng, Yumin Webster, Richard M. Powell, James Waters, Raymond Reed, Simon H. |
author_sort | Bennett, Mark |
collection | PubMed |
description | ChIP-chip is a microarray based technology for determining the genomic locations of chromatin bound factors of interest, such as proteins. Standard ChIP-chip analyses employ peak detection methodologies to generate lists of genomic binding sites. No previously published method exists to enable comparative analyses of enrichment levels derived from datasets examining different experimental conditions. This restricts the use of the technology to binary comparisons of presence or absence of features between datasets. Here we present the R package Sandcastle — Software for the Analysis and Normalisation of Data from ChIP-chip AssayS of Two or more Linked Experiments — which allows for comparative analyses of data from multiple experiments by normalising all datasets to a common background. Relative changes in binding levels between experimental datasets can thus be determined, enabling the extraction of latent information from ChIP-chip experiments. Novel enrichment detection and peak calling algorithms are also presented, with a range of graphical tools, which facilitate these analyses. The software and documentation are available for download from http://reedlab.cardiff.ac.uk/sandcastle. |
format | Online Article Text |
id | pubmed-4549617 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-45496172015-08-26 Sandcastle: software for revealing latent information in multiple experimental ChIP-chip datasets via a novel normalisation procedure Bennett, Mark Evans, Katie Ellen Yu, Shirong Teng, Yumin Webster, Richard M. Powell, James Waters, Raymond Reed, Simon H. Sci Rep Article ChIP-chip is a microarray based technology for determining the genomic locations of chromatin bound factors of interest, such as proteins. Standard ChIP-chip analyses employ peak detection methodologies to generate lists of genomic binding sites. No previously published method exists to enable comparative analyses of enrichment levels derived from datasets examining different experimental conditions. This restricts the use of the technology to binary comparisons of presence or absence of features between datasets. Here we present the R package Sandcastle — Software for the Analysis and Normalisation of Data from ChIP-chip AssayS of Two or more Linked Experiments — which allows for comparative analyses of data from multiple experiments by normalising all datasets to a common background. Relative changes in binding levels between experimental datasets can thus be determined, enabling the extraction of latent information from ChIP-chip experiments. Novel enrichment detection and peak calling algorithms are also presented, with a range of graphical tools, which facilitate these analyses. The software and documentation are available for download from http://reedlab.cardiff.ac.uk/sandcastle. Nature Publishing Group 2015-08-26 /pmc/articles/PMC4549617/ /pubmed/26307543 http://dx.doi.org/10.1038/srep13395 Text en Copyright © 2015, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Bennett, Mark Evans, Katie Ellen Yu, Shirong Teng, Yumin Webster, Richard M. Powell, James Waters, Raymond Reed, Simon H. Sandcastle: software for revealing latent information in multiple experimental ChIP-chip datasets via a novel normalisation procedure |
title | Sandcastle: software for revealing latent information in multiple experimental ChIP-chip datasets via a novel normalisation procedure |
title_full | Sandcastle: software for revealing latent information in multiple experimental ChIP-chip datasets via a novel normalisation procedure |
title_fullStr | Sandcastle: software for revealing latent information in multiple experimental ChIP-chip datasets via a novel normalisation procedure |
title_full_unstemmed | Sandcastle: software for revealing latent information in multiple experimental ChIP-chip datasets via a novel normalisation procedure |
title_short | Sandcastle: software for revealing latent information in multiple experimental ChIP-chip datasets via a novel normalisation procedure |
title_sort | sandcastle: software for revealing latent information in multiple experimental chip-chip datasets via a novel normalisation procedure |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4549617/ https://www.ncbi.nlm.nih.gov/pubmed/26307543 http://dx.doi.org/10.1038/srep13395 |
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