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miRMaster 2.0: multi-species non-coding RNA sequencing analyses at scale
Analyzing all features of small non-coding RNA sequencing data can be demanding and challenging. To facilitate this process, we developed miRMaster. After the analysis of over 125 000 human samples and 1.5 trillion human small RNA reads over 4 years, we present miRMaster 2 with a wide range of updat...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8262700/ https://www.ncbi.nlm.nih.gov/pubmed/33872372 http://dx.doi.org/10.1093/nar/gkab268 |
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author | Fehlmann, Tobias Kern, Fabian Laham, Omar Backes, Christina Solomon, Jeffrey Hirsch, Pascal Volz, Carsten Müller, Rolf Keller, Andreas |
author_facet | Fehlmann, Tobias Kern, Fabian Laham, Omar Backes, Christina Solomon, Jeffrey Hirsch, Pascal Volz, Carsten Müller, Rolf Keller, Andreas |
author_sort | Fehlmann, Tobias |
collection | PubMed |
description | Analyzing all features of small non-coding RNA sequencing data can be demanding and challenging. To facilitate this process, we developed miRMaster. After the analysis of over 125 000 human samples and 1.5 trillion human small RNA reads over 4 years, we present miRMaster 2 with a wide range of updates and new features. We extended our reference data sets so that miRMaster 2 now supports the analysis of eight species (e.g. human, mouse, chicken, dog, cow) and 10 non-coding RNA classes (e.g. microRNAs, piRNAs, tRNAs, rRNAs, circRNAs). We also incorporated new downstream analysis modules such as batch effect analysis or sample embeddings using UMAP, and updated annotation data bases included by default (miRBase, Ensembl, GtRNAdb). To accommodate the increasing popularity of single cell small-RNA sequencing data, we incorporated a module for unique molecular identifier (UMI) processing. Further, the output tables and graphics have been improved based on user feedback and new output formats that emerged in the community are now supported (e.g. miRGFF3). Finally, we integrated differential expression analysis with the miRNA enrichment analysis tool miEAA. miRMaster is freely available at https://www.ccb.uni-saarland.de/mirmaster2. |
format | Online Article Text |
id | pubmed-8262700 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-82627002021-07-08 miRMaster 2.0: multi-species non-coding RNA sequencing analyses at scale Fehlmann, Tobias Kern, Fabian Laham, Omar Backes, Christina Solomon, Jeffrey Hirsch, Pascal Volz, Carsten Müller, Rolf Keller, Andreas Nucleic Acids Res Web Server Issue Analyzing all features of small non-coding RNA sequencing data can be demanding and challenging. To facilitate this process, we developed miRMaster. After the analysis of over 125 000 human samples and 1.5 trillion human small RNA reads over 4 years, we present miRMaster 2 with a wide range of updates and new features. We extended our reference data sets so that miRMaster 2 now supports the analysis of eight species (e.g. human, mouse, chicken, dog, cow) and 10 non-coding RNA classes (e.g. microRNAs, piRNAs, tRNAs, rRNAs, circRNAs). We also incorporated new downstream analysis modules such as batch effect analysis or sample embeddings using UMAP, and updated annotation data bases included by default (miRBase, Ensembl, GtRNAdb). To accommodate the increasing popularity of single cell small-RNA sequencing data, we incorporated a module for unique molecular identifier (UMI) processing. Further, the output tables and graphics have been improved based on user feedback and new output formats that emerged in the community are now supported (e.g. miRGFF3). Finally, we integrated differential expression analysis with the miRNA enrichment analysis tool miEAA. miRMaster is freely available at https://www.ccb.uni-saarland.de/mirmaster2. Oxford University Press 2021-04-19 /pmc/articles/PMC8262700/ /pubmed/33872372 http://dx.doi.org/10.1093/nar/gkab268 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Web Server Issue Fehlmann, Tobias Kern, Fabian Laham, Omar Backes, Christina Solomon, Jeffrey Hirsch, Pascal Volz, Carsten Müller, Rolf Keller, Andreas miRMaster 2.0: multi-species non-coding RNA sequencing analyses at scale |
title | miRMaster 2.0: multi-species non-coding RNA sequencing analyses at scale |
title_full | miRMaster 2.0: multi-species non-coding RNA sequencing analyses at scale |
title_fullStr | miRMaster 2.0: multi-species non-coding RNA sequencing analyses at scale |
title_full_unstemmed | miRMaster 2.0: multi-species non-coding RNA sequencing analyses at scale |
title_short | miRMaster 2.0: multi-species non-coding RNA sequencing analyses at scale |
title_sort | mirmaster 2.0: multi-species non-coding rna sequencing analyses at scale |
topic | Web Server Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8262700/ https://www.ncbi.nlm.nih.gov/pubmed/33872372 http://dx.doi.org/10.1093/nar/gkab268 |
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