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Repliscan: a tool for classifying replication timing regions

BACKGROUND: Replication timing experiments that use label incorporation and high throughput sequencing produce peaked data similar to ChIP-Seq experiments. However, the differences in experimental design, coverage density, and possible results make traditional ChIP-Seq analysis methods inappropriate...

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Autores principales: Zynda, Gregory J., Song, Jawon, Concia, Lorenzo, Wear, Emily E., Hanley-Bowdoin, Linda, Thompson, William F., Vaughn, Matthew W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5547489/
https://www.ncbi.nlm.nih.gov/pubmed/28784090
http://dx.doi.org/10.1186/s12859-017-1774-x
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author Zynda, Gregory J.
Song, Jawon
Concia, Lorenzo
Wear, Emily E.
Hanley-Bowdoin, Linda
Thompson, William F.
Vaughn, Matthew W.
author_facet Zynda, Gregory J.
Song, Jawon
Concia, Lorenzo
Wear, Emily E.
Hanley-Bowdoin, Linda
Thompson, William F.
Vaughn, Matthew W.
author_sort Zynda, Gregory J.
collection PubMed
description BACKGROUND: Replication timing experiments that use label incorporation and high throughput sequencing produce peaked data similar to ChIP-Seq experiments. However, the differences in experimental design, coverage density, and possible results make traditional ChIP-Seq analysis methods inappropriate for use with replication timing. RESULTS: To accurately detect and classify regions of replication across the genome, we present Repliscan. Repliscan robustly normalizes, automatically removes outlying and uninformative data points, and classifies Repli-seq signals into discrete combinations of replication signatures. The quality control steps and self-fitting methods make Repliscan generally applicable and more robust than previous methods that classify regions based on thresholds. CONCLUSIONS: Repliscan is simple and effective to use on organisms with different genome sizes. Even with analysis window sizes as small as 1 kilobase, reliable profiles can be generated with as little as 2.4x coverage.
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spelling pubmed-55474892017-08-09 Repliscan: a tool for classifying replication timing regions Zynda, Gregory J. Song, Jawon Concia, Lorenzo Wear, Emily E. Hanley-Bowdoin, Linda Thompson, William F. Vaughn, Matthew W. BMC Bioinformatics Software BACKGROUND: Replication timing experiments that use label incorporation and high throughput sequencing produce peaked data similar to ChIP-Seq experiments. However, the differences in experimental design, coverage density, and possible results make traditional ChIP-Seq analysis methods inappropriate for use with replication timing. RESULTS: To accurately detect and classify regions of replication across the genome, we present Repliscan. Repliscan robustly normalizes, automatically removes outlying and uninformative data points, and classifies Repli-seq signals into discrete combinations of replication signatures. The quality control steps and self-fitting methods make Repliscan generally applicable and more robust than previous methods that classify regions based on thresholds. CONCLUSIONS: Repliscan is simple and effective to use on organisms with different genome sizes. Even with analysis window sizes as small as 1 kilobase, reliable profiles can be generated with as little as 2.4x coverage. BioMed Central 2017-08-07 /pmc/articles/PMC5547489/ /pubmed/28784090 http://dx.doi.org/10.1186/s12859-017-1774-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 Software
Zynda, Gregory J.
Song, Jawon
Concia, Lorenzo
Wear, Emily E.
Hanley-Bowdoin, Linda
Thompson, William F.
Vaughn, Matthew W.
Repliscan: a tool for classifying replication timing regions
title Repliscan: a tool for classifying replication timing regions
title_full Repliscan: a tool for classifying replication timing regions
title_fullStr Repliscan: a tool for classifying replication timing regions
title_full_unstemmed Repliscan: a tool for classifying replication timing regions
title_short Repliscan: a tool for classifying replication timing regions
title_sort repliscan: a tool for classifying replication timing regions
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5547489/
https://www.ncbi.nlm.nih.gov/pubmed/28784090
http://dx.doi.org/10.1186/s12859-017-1774-x
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