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Threshold-seq: a tool for determining the threshold in short RNA-seq datasets
SUMMARY: We present ‘Threshold-seq,’ a new approach for determining thresholds in deep-sequencing datasets of short RNA transcripts. Threshold-seq addresses the critical question of how many reads need to support a short RNA molecule in a given dataset before it can be considered different from ‘bac...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5870860/ https://www.ncbi.nlm.nih.gov/pubmed/28203700 http://dx.doi.org/10.1093/bioinformatics/btx073 |
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author | Magee, Rogan Loher, Phillipe Londin, Eric Rigoutsos, Isidore |
author_facet | Magee, Rogan Loher, Phillipe Londin, Eric Rigoutsos, Isidore |
author_sort | Magee, Rogan |
collection | PubMed |
description | SUMMARY: We present ‘Threshold-seq,’ a new approach for determining thresholds in deep-sequencing datasets of short RNA transcripts. Threshold-seq addresses the critical question of how many reads need to support a short RNA molecule in a given dataset before it can be considered different from ‘background.’ The proposed scheme is easy to implement and incorporate into existing pipelines. AVAILABILITY AND IMPLEMENTATION: Source code of Threshold-seq is freely available as an R package at: http://cm.jefferson.edu/threshold-seq/ SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-5870860 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-58708602018-03-29 Threshold-seq: a tool for determining the threshold in short RNA-seq datasets Magee, Rogan Loher, Phillipe Londin, Eric Rigoutsos, Isidore Bioinformatics Applications Notes SUMMARY: We present ‘Threshold-seq,’ a new approach for determining thresholds in deep-sequencing datasets of short RNA transcripts. Threshold-seq addresses the critical question of how many reads need to support a short RNA molecule in a given dataset before it can be considered different from ‘background.’ The proposed scheme is easy to implement and incorporate into existing pipelines. AVAILABILITY AND IMPLEMENTATION: Source code of Threshold-seq is freely available as an R package at: http://cm.jefferson.edu/threshold-seq/ SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2017-07-01 2017-02-14 /pmc/articles/PMC5870860/ /pubmed/28203700 http://dx.doi.org/10.1093/bioinformatics/btx073 Text en © The Author 2017. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Applications Notes Magee, Rogan Loher, Phillipe Londin, Eric Rigoutsos, Isidore Threshold-seq: a tool for determining the threshold in short RNA-seq datasets |
title | Threshold-seq: a tool for determining the threshold in short RNA-seq datasets |
title_full | Threshold-seq: a tool for determining the threshold in short RNA-seq datasets |
title_fullStr | Threshold-seq: a tool for determining the threshold in short RNA-seq datasets |
title_full_unstemmed | Threshold-seq: a tool for determining the threshold in short RNA-seq datasets |
title_short | Threshold-seq: a tool for determining the threshold in short RNA-seq datasets |
title_sort | threshold-seq: a tool for determining the threshold in short rna-seq datasets |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5870860/ https://www.ncbi.nlm.nih.gov/pubmed/28203700 http://dx.doi.org/10.1093/bioinformatics/btx073 |
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