Metatranscriptomic RNA-Seq Data Analysis of Virus-Infected Host Cells.

Nooran Abu Mazen, Jessica Luc, Briallen Lobb, Jeremy Alexander Hirota, Arinjay Banerjee, Andrew C Doxey

Abstract read

In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Nooran Abu MazenDepartment of Biology, University of Waterloo, Waterloo, ON, Canada.

Jessica LucDepartment of Biology, University of Waterloo, Waterloo, ON, Canada.

Briallen LobbDepartment of Biology, University of Waterloo, Waterloo, ON, Canada.

Jeremy Alexander HirotaDepartment of Biology, University of Waterloo, Waterloo, ON, Canada.

Arinjay BanerjeeDepartment of Biology, University of Waterloo, Waterloo, ON, Canada.

Andrew C DoxeyDepartment of Biology, University of Waterloo, Waterloo, ON, Canada. acdoxey@uwaterloo.ca.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

RNA sequencing (RNA-seq) analysis of virus-infected host cells enables researchers to study a wide range of phenomena involving host-virus interactions. This includes genomic analysis of the viral population itself, as well as analysis of the transcriptional dynamics of the virus and host during infection. In this chapter, we provide a guide for researchers interested in performing RNA-seq data analysis of virus-infected host cells or cell lines. We outline several bioinformatic protocols for quantifying viral abundance, assembling viral genomes from mixed samples, and performing differential expression analysis, among other common workflows. These workflows can be used as starting points for researchers aiming to analyze RNA-seq datasets of mixed samples containing both host and viral RNA, such as virus-infected cell lines or clinical samples.

Indexed as

Computational BiologyRNA-SeqCell LineGene Expression ProfilingGenome, ViralHigh-Throughput Nucleotide SequencingHost-Pathogen InteractionsHumansRNA, ViralSequence Analysis, RNASoftwareTranscriptomeVirus DiseasesVirusesRNA, ViralBioinformaticsBioinformaticsHost response to virusMetatranscriptomicsRNA sequencingTaxonomic profilingViral abundanceViral genome assemblyViral infectionViral strain variation

Identifiers

PMID38888771

DOI10.1038/nrg3068

What OpenQuestion holds

Textmetadata

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Registered trials

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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.