ArticleBriefings in bioinformatics2021
Anti-bias training for (sc)RNA-seq: experimental and computational approaches to improve precision.
Article in Briefings in bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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.
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Who cites it
11 citing papers in PubMed.
- A single-cell transcriptome atlas reveals paradoxical monoallelic expression of RNA editing and heterozygous SNPs.Nucleic acids research · 2026Article
- Deep structural clustering reveals hidden systematic biases in RNA sequencing data.Genome research · 2025Article
- Cell Storage Conditions Impact Single-Cell Proteomic Landscapes.Journal of proteome research · 2025Article
- Machine learning-optimized targeted detection of alternative splicing.Nucleic acids research · 2025Article
- Machine learning-optimized targeted detection of alternative splicing.bioRxiv : the preprint server for biology · 2024Article
- Status of single-cell RNA sequencing for reproductive toxicology in zebrafish and the transcriptomic trade-off.Current opinion in toxicology · 2024Article
- Understanding tumour endothelial cell heterogeneity and function from single-cell omics.Nature reviews. Cancer · 2023Review
- Modelling capture efficiency of single-cell RNA-sequencing data improves inference of transcriptome-wide burst kinetics.Bioinformatics (Oxford, England) · 2023Article
- Transcriptomics for Clinical and Experimental Biology Research: Hang on a Seq.Advanced genetics (Hoboken, N.J.) · 2023Review
- Computational approaches in rheumatic diseases - Deciphering complex spatio-temporal cell interactions.Computational and structural biotechnology journal · 2023Review
- Comparative Toxicotranscriptomics of Single Cell RNA-Seq and Conventional RNA-Seq in TCDD-Exposed Testicular Tissue.Frontiers in toxicology · 2022Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
RNA-seq, including single cell RNA-seq (scRNA-seq), is plagued by insufficient sensitivity and lack of precision. As a result, the full potential of (sc)RNA-seq is limited. Major factors in this respect are the presence of global bias in most datasets, which affects detection and quantitation of RNA in a length-dependent fashion. In particular, scRNA-seq is affected by technical noise and a high rate of dropouts, where the vast majority of original transcripts is not converted into sequencing reads. We discuss these biases origins and implications, bioinformatics approaches to correct for them, and how biases can be exploited to infer characteristics of the sample preparation process, which in turn can be used to improve library preparation.
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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.