ArticleNucleic acids research2021
noisyR: enhancing biological signal in sequencing datasets by characterizing random technical noise.
Article in Nucleic acids research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- Decoding drug-responsive cell subpopulations in triple-negative breast cancer using single-cell multiomics.iScience · 2026Article
- Technical and biological sources of noise confound multiplexed enhancer AAV screening.Nature communications · 2026Article
- PCLIPtools: a robust framework for identifying RNA-protein interaction sites from PAR-CLIP experiments.Nucleic acids research · 2026Article
- Dynamic transcriptomic responses reveal candidate defense genes againstFrontiers in plant science · 2026Article
- Accelerating Maximum Likelihood Phylogenetic Inference via Early Stopping to Evade (Over-)optimization.Systematic biology · 2025Article
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- An RBPMS-driven splicing regulatory axis including MBNL1, RBFOX2, and QK promotes smooth muscle cell contractile identity.Nucleic acids research · 2025Article
- PCLIPtools: A Robust Framework for Identifying RNA-Protein Interaction Sites from PAR-CLIP experiments.bioRxiv : the preprint server for biology · 2025Article
- Patterns of extreme outlier gene expression suggest an edge of chaos effect in transcriptomic networks.Genome biology · 2025Article
- CHD8 interacts with BCL11A to induce oncogenic transcription in triple negative breast cancer.The EMBO journal · 2025Article
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- Transcriptomic profiling during normothermic machine perfusion of human kidneys reveals a pro-inflammatory cellular landscape and gene expression signature associated with severe ischemia-reperfusion injury and delayed graft function.Frontiers in immunology · 2025Article
- Comparative RNA profiling identifies stage-specific phasiRNAs and coexpressed Argonaute genes in Bambusoideae and Pooideae species.The Plant cell · 2024Article
- A transcriptomic hourglass in brown algae.Nature · 2024Article
- Denoiseit: denoising gene expression data using rank based isolation trees.BMC bioinformatics · 2024Article
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- Proinflammatory cytokines driving cardiotoxicity in COVID-19.Cardiovascular research · 2024Article
- Drug target prediction through deep learning functional representation of gene signatures.Nature communications · 2024Article
- Human pancreatic islet microRNAs implicated in diabetes and related traits by large-scale genetic analysis.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
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7 authors.
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Abstract
High-throughput sequencing enables an unprecedented resolution in transcript quantification, at the cost of magnifying the impact of technical noise. The consistent reduction of random background noise to capture functionally meaningful biological signals is still challenging. Intrinsic sequencing variability introducing low-level expression variations can obscure patterns in downstream analyses. We introduce noisyR, a comprehensive noise filter to assess the variation in signal distribution and achieve an optimal information-consistency across replicates and samples; this selection also facilitates meaningful pattern recognition outside the background-noise range. noisyR is applicable to count matrices and sequencing data; it outputs sample-specific signal/noise thresholds and filtered expression matrices. We exemplify the effects of minimizing technical noise on several datasets, across various sequencing assays: coding, non-coding RNAs and interactions, at bulk and single-cell level. An immediate consequence of filtering out noise is the convergence of predictions (differential-expression calls, enrichment analyses and inference of gene regulatory networks) across different approaches.
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