ArticleBriefings in bioinformatics2023
CODA: a combo-Seq data analysis workflow.
Article in Briefings in bioinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed, 2 citations in OpenAlex.
- Investigation of the effects of phthalates onFrontiers in endocrinology · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 2 countries.
Funding
Abstract
The analysis of the combined mRNA and miRNA content of a biological sample can be of interest for answering several research questions, like biomarkers discovery, or mRNA-miRNA interactions. However, the process is costly and time-consuming, separate libraries need to be prepared and sequenced on different flowcells. Combo-Seq is a library prep kit that allows us to prepare combined mRNA-miRNA libraries starting from very low total RNA. To date, no dedicated bioinformatics method exists for the processing of Combo-Seq data. In this paper, we describe CODA (Combo-seq Data Analysis), a workflow specifically developed for the processing of Combo-Seq data that employs existing free-to-use tools. We compare CODA with exceRpt, the pipeline suggested by the kit manufacturer for this purpose. We also evaluate how Combo-Seq libraries analysed with CODA perform compared with conventional poly(A) and small RNA libraries prepared from the same samples. We show that using CODA more successfully trimmed reads are recovered compared with exceRpt, and the difference is more dramatic with short sequencing reads. We demonstrate how Combo-Seq identifies as many genes and fewer miRNAs compared to the standard libraries, and how miRNA validation favours conventional small RNA libraries over Combo-Seq. The CODA code is available at https://github.com/marta-nazzari/CODA.
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Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.