ArticleNucleic acids research2016
ROTS: reproducible RNA-seq biomarker detector-prognostic markers for clear cell renal cell cancer.
Article in Nucleic acids research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.
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Who cites it
37 citing papers in PubMed.
- Transcriptomics of type 1 diabetes progression: a validation study in newly diagnosed patients.EBioMedicine · 2026Article
- Clarifying the scope and capabilities of ROTS in differential expression analysis.Bioinformatics (Oxford, England) · 2026Article
- REACTOR: REgulon Activity analysis and Comparison Tool for single-cell transcriptOmics Research.Bioinformatics (Oxford, England) · 2026Article
- Revisiting differential expression analysis: An updated six-dimensional comparative study.PloS one · 2026Article
- Assessing the impact of transcriptomics data analysis pipelines on downstream functional enrichment results.Nucleic acids research · 2024Article
- Reduced interleukin-18 secretion by human monocytic cells in response to infections with hyper-virulent Streptococcus pyogenes.Journal of biomedical science · 2024Article
- Gene expression signature predicts rate of type 1 diabetes progression.EBioMedicine · 2023Article
- Two-sample test with g-modeling and its applications.Statistics in medicine · 2023Article
- Benchmarking tools for detecting longitudinal differential expression in proteomics data allows establishing a robust reproducibility optimization regression approach.Nature communications · 2022Article
- The balance between NANOG and SOX17 mediated by TET proteins regulates specification of human primordial germ cell fate.Cell & bioscience · 2022Article
- Differential Expression Analysis of Single-Cell RNA-Seq Data: Current Statistical Approaches and Outstanding Challenges.Entropy (Basel, Switzerland) · 2022Review
- Persistent coxsackievirus B1 infection triggers extensive changes in the transcriptome of human pancreatic ductal cells.iScience · 2022Article
- Optimization of metabolomic data processing using NOREVA.Nature protocols · 2022Review
- COVID-19-specific transcriptomic signature detectable in blood across multiple cohorts.Frontiers in genetics · 2022Article
- Pancreas Whole Tissue Transcriptomics Highlights the Role of the Exocrine Pancreas in Patients With Recently Diagnosed Type 1 Diabetes.Frontiers in endocrinology · 2022Article
- Article
- Dissecting immune cell stat regulation network reveals biomarkers to predict ICB therapy responders in melanoma.Journal of translational medicine · 2021Article
- Diversity and intratumoral heterogeneity in human gallbladder cancer progression revealed by single-cell RNA sequencing.Clinical and translational medicine · 2021Article
- Characterization of the interleukin-17 effect on articular cartilage in a translational model: an explorative study.BMC rheumatology · 2020Article
- Benchmarking RNA-seq differential expression analysis methods using spike-in and simulation data.PloS one · 2020Article
Corrections and comments
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4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recent comprehensive assessments of RNA-seq technology support its utility in quantifying gene expression in various samples. The next step of rigorously quantifying differences between sample groups, however, still lacks well-defined best practices. Although a number of advanced statistical methods have been developed, several studies demonstrate that their performance depends strongly on the data under analysis, which compromises practical utility in real biomedical studies. As a solution, we propose to use a data-adaptive procedure that selects an optimal statistic capable of maximizing reproducibility of detections. After demonstrating its improved sensitivity and specificity in a controlled spike-in study, the utility of the procedure is confirmed in a real biomedical study by identifying prognostic markers for clear cell renal cell carcinoma (ccRCC). In addition to identifying several genes previously associated with ccRCC prognosis, several potential new biomarkers among genes regulating cell growth, metabolism and solute transport were detected.
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