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Correcting nucleotide-specific biases in high-throughput sequencing data
BACKGROUND: High-throughput sequence (HTS) data exhibit position-specific nucleotide biases that obscure the intended signal and reduce the effectiveness of these data for downstream analyses. These biases are particularly evident in HTS assays for identifying regulatory regions in DNA (DNase-seq, C...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5540620/ https://www.ncbi.nlm.nih.gov/pubmed/28764645 http://dx.doi.org/10.1186/s12859-017-1766-x |
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author | Wang, Jeremy R. Quach, Bryan Furey, Terrence S. |
author_facet | Wang, Jeremy R. Quach, Bryan Furey, Terrence S. |
author_sort | Wang, Jeremy R. |
collection | PubMed |
description | BACKGROUND: High-throughput sequence (HTS) data exhibit position-specific nucleotide biases that obscure the intended signal and reduce the effectiveness of these data for downstream analyses. These biases are particularly evident in HTS assays for identifying regulatory regions in DNA (DNase-seq, ChIP-seq, FAIRE-seq, ATAC-seq). Biases may result from many experiment-specific factors, including selectivity of DNA restriction enzymes and fragmentation method, as well as sequencing technology-specific factors, such as choice of adapters/primers and sample amplification methods. RESULTS: We present a novel method to detect and correct position-specific nucleotide biases in HTS short read data. Our method calculates read-specific weights based on aligned reads to correct the over- or underrepresentation of position-specific nucleotide subsequences, both within and adjacent to the aligned read, relative to a baseline calculated in assay-specific enriched regions. Using HTS data from a variety of ChIP-seq, DNase-seq, FAIRE-seq, and ATAC-seq experiments, we show that our weight-adjusted reads reduce the position-specific nucleotide imbalance across reads and improve the utility of these data for downstream analyses, including identification and characterization of open chromatin peaks and transcription-factor binding sites. CONCLUSIONS: A general-purpose method to characterize and correct position-specific nucleotide sequence biases fills the need to recognize and deal with, in a systematic manner, binding-site preference for the growing number of HTS-based epigenetic assays. As the breadth and impact of these biases are better understood, the availability of a standard toolkit to correct them will be important. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-017-1766-x) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5540620 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-55406202017-08-07 Correcting nucleotide-specific biases in high-throughput sequencing data Wang, Jeremy R. Quach, Bryan Furey, Terrence S. BMC Bioinformatics Methodology Article BACKGROUND: High-throughput sequence (HTS) data exhibit position-specific nucleotide biases that obscure the intended signal and reduce the effectiveness of these data for downstream analyses. These biases are particularly evident in HTS assays for identifying regulatory regions in DNA (DNase-seq, ChIP-seq, FAIRE-seq, ATAC-seq). Biases may result from many experiment-specific factors, including selectivity of DNA restriction enzymes and fragmentation method, as well as sequencing technology-specific factors, such as choice of adapters/primers and sample amplification methods. RESULTS: We present a novel method to detect and correct position-specific nucleotide biases in HTS short read data. Our method calculates read-specific weights based on aligned reads to correct the over- or underrepresentation of position-specific nucleotide subsequences, both within and adjacent to the aligned read, relative to a baseline calculated in assay-specific enriched regions. Using HTS data from a variety of ChIP-seq, DNase-seq, FAIRE-seq, and ATAC-seq experiments, we show that our weight-adjusted reads reduce the position-specific nucleotide imbalance across reads and improve the utility of these data for downstream analyses, including identification and characterization of open chromatin peaks and transcription-factor binding sites. CONCLUSIONS: A general-purpose method to characterize and correct position-specific nucleotide sequence biases fills the need to recognize and deal with, in a systematic manner, binding-site preference for the growing number of HTS-based epigenetic assays. As the breadth and impact of these biases are better understood, the availability of a standard toolkit to correct them will be important. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-017-1766-x) contains supplementary material, which is available to authorized users. BioMed Central 2017-08-01 /pmc/articles/PMC5540620/ /pubmed/28764645 http://dx.doi.org/10.1186/s12859-017-1766-x Text en © The Author(s) 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Methodology Article Wang, Jeremy R. Quach, Bryan Furey, Terrence S. Correcting nucleotide-specific biases in high-throughput sequencing data |
title | Correcting nucleotide-specific biases in high-throughput sequencing data |
title_full | Correcting nucleotide-specific biases in high-throughput sequencing data |
title_fullStr | Correcting nucleotide-specific biases in high-throughput sequencing data |
title_full_unstemmed | Correcting nucleotide-specific biases in high-throughput sequencing data |
title_short | Correcting nucleotide-specific biases in high-throughput sequencing data |
title_sort | correcting nucleotide-specific biases in high-throughput sequencing data |
topic | Methodology Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5540620/ https://www.ncbi.nlm.nih.gov/pubmed/28764645 http://dx.doi.org/10.1186/s12859-017-1766-x |
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