Cargando…
Controlling taxa abundance improves metatranscriptomics differential analysis
BACKGROUND: A common task in analyzing metatranscriptomics data is to identify microbial metabolic pathways with differential RNA abundances across multiple sample groups. With information from paired metagenomics data, some differential methods control for either DNA or taxa abundances to address t...
Autores principales: | , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9990291/ https://www.ncbi.nlm.nih.gov/pubmed/36882742 http://dx.doi.org/10.1186/s12866-023-02799-9 |
_version_ | 1784901909147025408 |
---|---|
author | Ji, Zhicheng Ma, Li |
author_facet | Ji, Zhicheng Ma, Li |
author_sort | Ji, Zhicheng |
collection | PubMed |
description | BACKGROUND: A common task in analyzing metatranscriptomics data is to identify microbial metabolic pathways with differential RNA abundances across multiple sample groups. With information from paired metagenomics data, some differential methods control for either DNA or taxa abundances to address their strong correlation with RNA abundance. However, it remains unknown if both factors need to be controlled for simultaneously. RESULTS: We discovered that when either DNA or taxa abundance is controlled for, RNA abundance still has a strong partial correlation with the other factor. In both simulation studies and a real data analysis, we demonstrated that controlling for both DNA and taxa abundances leads to superior performance compared to only controlling for one factor. CONCLUSIONS: To fully address the confounding effects in analyzing metatranscriptomics data, both DNA and taxa abundances need to be controlled for in the differential analysis. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12866-023-02799-9. |
format | Online Article Text |
id | pubmed-9990291 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-99902912023-03-08 Controlling taxa abundance improves metatranscriptomics differential analysis Ji, Zhicheng Ma, Li BMC Microbiol Research Article BACKGROUND: A common task in analyzing metatranscriptomics data is to identify microbial metabolic pathways with differential RNA abundances across multiple sample groups. With information from paired metagenomics data, some differential methods control for either DNA or taxa abundances to address their strong correlation with RNA abundance. However, it remains unknown if both factors need to be controlled for simultaneously. RESULTS: We discovered that when either DNA or taxa abundance is controlled for, RNA abundance still has a strong partial correlation with the other factor. In both simulation studies and a real data analysis, we demonstrated that controlling for both DNA and taxa abundances leads to superior performance compared to only controlling for one factor. CONCLUSIONS: To fully address the confounding effects in analyzing metatranscriptomics data, both DNA and taxa abundances need to be controlled for in the differential analysis. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12866-023-02799-9. BioMed Central 2023-03-07 /pmc/articles/PMC9990291/ /pubmed/36882742 http://dx.doi.org/10.1186/s12866-023-02799-9 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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, visit http://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 | Research Article Ji, Zhicheng Ma, Li Controlling taxa abundance improves metatranscriptomics differential analysis |
title | Controlling taxa abundance improves metatranscriptomics differential analysis |
title_full | Controlling taxa abundance improves metatranscriptomics differential analysis |
title_fullStr | Controlling taxa abundance improves metatranscriptomics differential analysis |
title_full_unstemmed | Controlling taxa abundance improves metatranscriptomics differential analysis |
title_short | Controlling taxa abundance improves metatranscriptomics differential analysis |
title_sort | controlling taxa abundance improves metatranscriptomics differential analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9990291/ https://www.ncbi.nlm.nih.gov/pubmed/36882742 http://dx.doi.org/10.1186/s12866-023-02799-9 |
work_keys_str_mv | AT jizhicheng controllingtaxaabundanceimprovesmetatranscriptomicsdifferentialanalysis AT mali controllingtaxaabundanceimprovesmetatranscriptomicsdifferentialanalysis |