ArticleNAR cancer2021
On the impact of batch effect correction in TCGA isomiR expression data.
Article in NAR cancer, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 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
19 citing papers in PubMed.
- Response to commentary on 'CorrAdjust unveils biologically relevant transcriptomic correlations by efficiently eliminating hidden confounders'.Nucleic acids research · 2026Article
- Development and validation of a miRNA-based prognostic model for high-grade serous ovarian cancer: a retrospective cohort study.Lancet regional health. Americas · 2026Article
- Integration of artificial intelligence and multi-omics for precision medicine.Functional & integrative genomics · 2026Review
- miRNA gene mutations commonly disrupt the proper functioning of miRNA genes.Science advances · 2026Article
- Several novel classes of small regulatory RNAs show widespread changes in schizophrenia and bipolar disorder and extensive linkages to critical brain processes.Translational psychiatry · 2026Article
- AI in Cancer Prognosis: A Systematic Review of Multimodal Models Combining Pathology Images and High-Throughput Omics.Cancer informatics · 2026Article
- A Protocol for Weighted Gene Co-expression Network Analysis With Module Preservation and Functional Enrichment Analysis for Tumor and Normal Transcriptomic Data.Bio-protocol · 2025Article
- Charting the equine miRNA landscape: An integrated pipeline and browser for annotating, quantifying, and visualizing expression.PLoS genetics · 2025Article
- CorrAdjust unveils biologically relevant transcriptomic correlations by efficiently eliminating hidden confounders.Nucleic acids research · 2025Article
- Selective arm-usage of pre-miR-1307 dysregulates angiogenesis and affects breast cancer aggressiveness.BMC biology · 2025Article
- Post-Transcriptional Modifications to miRNAs Undergo Widespread Alterations, Creating a Unique Lung Adenocarcinoma IsomiRome.Cancers · 2024Article
- In search of the ratio of miRNA expression as robust biomarkers for constructing stable diagnostic models among multi-center data.Frontiers in genetics · 2024Article
- Pan-Cancer Analysis of Canonical and Modified miRNAs Enhances the Resolution of the Functional miRNAome in Cancer.Cancer research · 2022Article
- 5'isomiR-183-5p|+2 elicits tumor suppressor activity in a negative feedback loop with E2F1.Journal of experimental & clinical cancer research : CR · 2022Article
- Protocol for integrative subtyping of lower-grade gliomas using the SUMO pipeline.STAR protocols · 2022Article
- Article
- Identification of Novel Tumor Microenvironment Regulating Factor That Facilitates Tumor Immune Infiltration in Cervical Cancer.Frontiers in oncology · 2022Article
- Coordinated regulation of WNT/β-catenin, c-Met, and integrin signalling pathways by miR-193b controls triple negative breast cancer metastatic traits.BMC cancer · 2021Article
- Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
MicroRNAs (miRNAs) are small non-coding RNAs with diverse functions in post-transcriptional regulation of gene expression. Sequence and length variants of miRNAs are called isomiRs and can exert different functions compared to their canonical counterparts. The Cancer Genome Atlas (TCGA) provides isomiR-level expression data for patients of various cancer entities collected in a multi-center approach over several years. However, the impact of batch effects within individual cohorts has not been systematically investigated and corrected for before. Therefore, the aim of this study was to identify relevant cohort-specific batch variables and generate batch-corrected isomiR expression data for 16 TCGA cohorts. The main batch variables included sequencing platform, plate, sample purity and sequencing depth. Platform bias was related to certain length and sequence features of individual recurrently affected isomiRs. Furthermore, significant downregulation of reported tumor suppressive isomiRs in lung tumor tissue compared to normal samples was only observed after batch correction, highlighting the importance of working with corrected data. Batch-corrected datasets for all cohorts including quality control are provided as supplement. In summary, this study reveals that batch effects present in the TCGA dataset might mask biologically relevant effects and provides a valuable resource for research on isomiRs in cancer (accessible through GEO: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE164767).
Identifiers
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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 Socratic graph.