Reverse engineering environmental metatranscriptomes clarifies best practices for eukaryotic assembly
BMC Bioinformatics, ISSN: 1471-2105, Vol: 24, Issue: 1, Page: 74
2023
- 5Citations
- 19Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Citations5
- Citation Indexes5
- CrossRef4
- Captures19
- Readers19
- 19
Article Description
Background: Diverse communities of microbial eukaryotes in the global ocean provide a variety of essential ecosystem services, from primary production and carbon flow through trophic transfer to cooperation via symbioses. Increasingly, these communities are being understood through the lens of omics tools, which enable high-throughput processing of diverse communities. Metatranscriptomics offers an understanding of near real-time gene expression in microbial eukaryotic communities, providing a window into community metabolic activity. Results: Here we present a workflow for eukaryotic metatranscriptome assembly, and validate the ability of the pipeline to recapitulate real and manufactured eukaryotic community-level expression data. We also include an open-source tool for simulating environmental metatranscriptomes for testing and validation purposes. We reanalyze previously published metatranscriptomic datasets using our metatranscriptome analysis approach. Conclusion: We determined that a multi-assembler approach improves eukaryotic metatranscriptome assembly based on recapitulated taxonomic and functional annotations from an in-silico mock community. The systematic validation of metatranscriptome assembly and annotation methods provided here is a necessary step to assess the fidelity of our community composition measurements and functional content assignments from eukaryotic metatranscriptomes.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85149503154&origin=inward; http://dx.doi.org/10.1186/s12859-022-05121-y; http://www.ncbi.nlm.nih.gov/pubmed/36869298; https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-022-05121-y; https://dx.doi.org/10.1186/s12859-022-05121-y
Springer Science and Business Media LLC
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