ReviewBioMed research international2021
Bias in RNA-seq Library Preparation: Current Challenges and Solutions.
Review in BioMed research international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 65 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
65 citing papers in PubMed.
- High-resolution profiling of bacterial transcriptomes by SEnd-seq.The Biochemical journal · 2026Review
- Measuring the change in deleterious mutation burden of barley germplasm conserved over one regeneration cycle.G3 (Bethesda, Md.) · 2026Article
- tRNA-Derived Small RNAs in Digestive Cancers: From Translational Regulation to Immune and Extracellular Communication.Cancer science · 2026Review
- A method of comprehensive sequencing analysis of the small RNA fragmentome (RiboMarker).RNA (New York, N.Y.) · 2026Article
- Dynamic regulation of long non-coding RNAs across asexual and gametocyte development inbioRxiv : the preprint server for biology · 2026Article
- Hijacking innate immunity to enhance mRNA therapeutics by blocking IFN-P-body-XRN1 axis-mediated degradation.Nature communications · 2026Article
- DNA and RNA-based amplicon sequencing of paired supragingival and dentin lesion plaque in children with severe early childhood caries.International journal of oral science · 2026Article
- A practical guide to targeted single-cell RNA sequencing technologies.Communications biology · 2026Review
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- A novel one-step multiplex PCR method (OS-MPCR) for efficient NGS library preparation in cancer.PloS one · 2026Article
- PeakPrime: a peak-guided primer design pipeline for target enrichment in 3'-end RNA-seq.Bioinformatics advances · 2026Article
- Standardized Protocols for Environmental Sample Collection: Minimizing Contamination and Preserving Microbial Community Integrity.Methods in molecular biology (Clifton, N.J.) · 2026Review
- RoCK and ROI: single-cell transcriptomics with multiplexed enrichment of selected transcripts and region-specific sequencing.Nature communications · 2025Article
- Harnessing plasma transcriptomics for non-invasive cancer biomarker identification: a comprehensive review.Discover oncology · 2025Review
- Next generation sequencing and beyond: a review of genomic sequencing methods.Functional & integrative genomics · 2025Article
- Regulation and functional analysis of BvMBF1c in response to Cercospora leaf spot (CLS) stresses in sugar beet (Beta vulgaris L.).BMC plant biology · 2025Article
- Sample Preparation for Multi-Omics Analysis: Considerations and Guidance for Identifying the Ideal Workflow.Proteomics · 2025Review
- Quantifying Soil Microbiome Abundance by Metatranscriptomics and Complementary Molecular Techniques-Cross-Validation and Perspectives.Molecular ecology resources · 2025Article
5 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Although RNA sequencing (RNA-seq) has become the most advanced technology for transcriptome analysis, it also confronts various challenges. As we all know, the workflow of RNA-seq is extremely complicated and it is easy to produce bias. This may damage the quality of RNA-seq dataset and lead to an incorrect interpretation for sequencing result. Thus, our detailed understanding of the source and nature of these biases is essential for the interpretation of RNA-seq data, finding methods to improve the quality of RNA-seq experimental, or development bioinformatics tools to compensate for these biases. Here, we discuss the sources of experimental bias in RNA-seq. And for each type of bias, we discussed the method for improvement, in order to provide some useful suggestions for researcher in RNA-seq experimental.
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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.