Controlling taxa abundance improves metatranscriptomics differential analysis
Abstract 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 a...
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| Format: | Article |
| Language: | English |
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BMC
2023-03-01
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| Series: | BMC Microbiology |
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| Online Access: | https://doi.org/10.1186/s12866-023-02799-9 |
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| author | Zhicheng Ji Li Ma |
| author_facet | Zhicheng Ji Li Ma |
| author_sort | Zhicheng Ji |
| collection | DOAJ |
| description | Abstract 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. |
| first_indexed | 2024-04-09T23:08:23Z |
| format | Article |
| id | doaj.art-6109be70dea6414f82ff6591829dbf7d |
| institution | Directory Open Access Journal |
| issn | 1471-2180 |
| language | English |
| last_indexed | 2024-04-09T23:08:23Z |
| publishDate | 2023-03-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Microbiology |
| spelling | doaj.art-6109be70dea6414f82ff6591829dbf7d2023-03-22T10:34:13ZengBMCBMC Microbiology1471-21802023-03-0123111010.1186/s12866-023-02799-9Controlling taxa abundance improves metatranscriptomics differential analysisZhicheng Ji0Li Ma1Department of Biostatistics and Bioinformatics, Duke UniversityDepartment of Biostatistics and Bioinformatics, Duke UniversityAbstract 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.https://doi.org/10.1186/s12866-023-02799-9MetatranscriptomicsShotgun sequencingMicrobiomeDifferential analysis |
| spellingShingle | Zhicheng Ji Li Ma Controlling taxa abundance improves metatranscriptomics differential analysis BMC Microbiology Metatranscriptomics Shotgun sequencing Microbiome 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 | Metatranscriptomics Shotgun sequencing Microbiome Differential analysis |
| url | https://doi.org/10.1186/s12866-023-02799-9 |
| work_keys_str_mv | AT zhichengji controllingtaxaabundanceimprovesmetatranscriptomicsdifferentialanalysis AT lima controllingtaxaabundanceimprovesmetatranscriptomicsdifferentialanalysis |