ArticleBMC bioinformatics2020
Short paired-end reads trump long single-end reads for expression analysis.
Article in BMC bioinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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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.
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Who cites it
11 citing papers in PubMed.
- The Vacc-SeqQC project: Benchmarking RNA-Seq for clinical vaccine studies.Frontiers in immunology · 2022Trial
- Designing RNA sequencing experiments: A practical guide to reproducible gene expression analysis.Computational and structural biotechnology journal · 2026Review
- Shear Stress Regulates Osteogenic Differentiation of Human Dental Pulp Stem Cells via the p38 Pathway.International journal of molecular sciences · 2025Article
- De novo assembly of transcriptomes and differential gene expression analysis using short-read data from emerging model organisms - a brief guide.Frontiers in zoology · 2024Review
- Review
- 11-Cl-BBQ, a select modulator of AhR-regulated transcription, suppresses lung cancer cell growth via activation of p53 and p27The FEBS journal · 2023Article
- Article
- Evaluation of methods to detect circular RNAs from single-end RNA-sequencing data.BMC genomics · 2022Article
- how_are_we_stranded_here: quick determination of RNA-Seq strandedness.BMC bioinformatics · 2022Article
- HRT Atlas v1.0 database: redefining human and mouse housekeeping genes and candidate reference transcripts by mining massive RNA-seq datasets.Nucleic acids research · 2021Article
- Bioinformatic Pipelines to Analyze lncRNAs RNAseq Data.Methods in molecular biology (Clifton, N.J.) · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTypical experimental design advice for expression analyses using RNA-seq generally assumes that single-end reads provide robust gene-level expression estimates in a cost-effective manner, and that the additional benefits obtained from paired-end sequencing are not worth the additional cost. However, in many cases (e.g., with Illumina NextSeq and NovaSeq instruments), shorter paired-end reads and longer single-end reads can be generated for the same cost, and it is not obvious which strategy should be preferred. Using publicly available data, we test whether short-paired end reads can achieve more robust expression estimates and differential expression results than single-end reads of approximately the same total number of sequenced bases.
resultsAt both the transcript and gene levels, 2 × 40 paired-end reads unequivocally provide expression estimates that are more highly correlated with 2 × 125 than 1 × 75 reads; in nearly all cases, those correlations are also greater than for 1 × 125, despite the greater total number of sequenced bases for the latter. Across an array of metrics, differential expression tests based upon 2 × 40 consistently outperform those using 1 × 75.
conclusionResearchers seeking a cost-effective approach for gene-level expression analysis should prefer short paired-end reads over a longer single-end strategy. Short paired-end reads will also give reasonably robust expression estimates and differential expression results at the isoform level.
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