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recount3: summaries and queries for large-scale RNA-seq expression and splicing
We present recount3, a resource consisting of over 750,000 publicly available human and mouse RNA sequencing (RNA-seq) samples uniformly processed by our new Monorail analysis pipeline. To facilitate access to the data, we provide the recount3 and snapcount R/Bioconductor packages as well as complem...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8628444/ https://www.ncbi.nlm.nih.gov/pubmed/34844637 http://dx.doi.org/10.1186/s13059-021-02533-6 |
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author | Wilks, Christopher Zheng, Shijie C. Chen, Feng Yong Charles, Rone Solomon, Brad Ling, Jonathan P. Imada, Eddie Luidy Zhang, David Joseph, Lance Leek, Jeffrey T. Jaffe, Andrew E. Nellore, Abhinav Collado-Torres, Leonardo Hansen, Kasper D. Langmead, Ben |
author_facet | Wilks, Christopher Zheng, Shijie C. Chen, Feng Yong Charles, Rone Solomon, Brad Ling, Jonathan P. Imada, Eddie Luidy Zhang, David Joseph, Lance Leek, Jeffrey T. Jaffe, Andrew E. Nellore, Abhinav Collado-Torres, Leonardo Hansen, Kasper D. Langmead, Ben |
author_sort | Wilks, Christopher |
collection | PubMed |
description | We present recount3, a resource consisting of over 750,000 publicly available human and mouse RNA sequencing (RNA-seq) samples uniformly processed by our new Monorail analysis pipeline. To facilitate access to the data, we provide the recount3 and snapcount R/Bioconductor packages as well as complementary web resources. Using these tools, data can be downloaded as study-level summaries or queried for specific exon-exon junctions, genes, samples, or other features. Monorail can be used to process local and/or private data, allowing results to be directly compared to any study in recount3. Taken together, our tools help biologists maximize the utility of publicly available RNA-seq data, especially to improve their understanding of newly collected data. recount3 is available from http://rna.recount.bio. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at (10.1186/s13059-021-02533-6). |
format | Online Article Text |
id | pubmed-8628444 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-86284442021-12-01 recount3: summaries and queries for large-scale RNA-seq expression and splicing Wilks, Christopher Zheng, Shijie C. Chen, Feng Yong Charles, Rone Solomon, Brad Ling, Jonathan P. Imada, Eddie Luidy Zhang, David Joseph, Lance Leek, Jeffrey T. Jaffe, Andrew E. Nellore, Abhinav Collado-Torres, Leonardo Hansen, Kasper D. Langmead, Ben Genome Biol Database We present recount3, a resource consisting of over 750,000 publicly available human and mouse RNA sequencing (RNA-seq) samples uniformly processed by our new Monorail analysis pipeline. To facilitate access to the data, we provide the recount3 and snapcount R/Bioconductor packages as well as complementary web resources. Using these tools, data can be downloaded as study-level summaries or queried for specific exon-exon junctions, genes, samples, or other features. Monorail can be used to process local and/or private data, allowing results to be directly compared to any study in recount3. Taken together, our tools help biologists maximize the utility of publicly available RNA-seq data, especially to improve their understanding of newly collected data. recount3 is available from http://rna.recount.bio. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at (10.1186/s13059-021-02533-6). BioMed Central 2021-11-29 /pmc/articles/PMC8628444/ /pubmed/34844637 http://dx.doi.org/10.1186/s13059-021-02533-6 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visithttp://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Database Wilks, Christopher Zheng, Shijie C. Chen, Feng Yong Charles, Rone Solomon, Brad Ling, Jonathan P. Imada, Eddie Luidy Zhang, David Joseph, Lance Leek, Jeffrey T. Jaffe, Andrew E. Nellore, Abhinav Collado-Torres, Leonardo Hansen, Kasper D. Langmead, Ben recount3: summaries and queries for large-scale RNA-seq expression and splicing |
title | recount3: summaries and queries for large-scale RNA-seq expression and splicing |
title_full | recount3: summaries and queries for large-scale RNA-seq expression and splicing |
title_fullStr | recount3: summaries and queries for large-scale RNA-seq expression and splicing |
title_full_unstemmed | recount3: summaries and queries for large-scale RNA-seq expression and splicing |
title_short | recount3: summaries and queries for large-scale RNA-seq expression and splicing |
title_sort | recount3: summaries and queries for large-scale rna-seq expression and splicing |
topic | Database |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8628444/ https://www.ncbi.nlm.nih.gov/pubmed/34844637 http://dx.doi.org/10.1186/s13059-021-02533-6 |
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