ArticleBMC genomics2018
Power in pairs: assessing the statistical value of paired samples in tests for differential expression.
Article in BMC genomics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.
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Who cites it
30 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A Systematic Review of MicroRNA Signatures Associated with the Progression of Leukoplakia with and without Epithelial Dysplasia.Biomolecules · 2021Pooled it
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- Longitudinal and Stability-Aware Analysis Reveals Treatment-Specific MicroRNA Response Signatures Following Immune-Reconstitution and B-Cell-Targeted Therapies in Multiple Sclerosis.International journal of molecular sciences · 2026Article
- Dysbiotic shift in the oral microbiota of patients with Alzheimer's disease compared to their healthy life partners-a combinatorial approach and a paired study design.Alzheimer's research & therapy · 2026Article
- Hampered CD8 + ILT2 + T cell activation by HLA-G suggests a new immune checkpoint in gastric adenocarcinoma.Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association · 2026Article
- A newFrontiers in toxicology · 2026Article
- Two Molecular Subgroups Predict Most Recurrences in Advanced Laryngeal Squamous Cell Carcinoma.Cancer research communications · 2026Article
- DEAD-Box Helicase 3 Modulates the Non-Coding RNA Pool in Ribonucleoprotein Condensates During Stress Granule Formation.Non-coding RNA · 2025Article
- Replicability of bulk RNA-Seq differential expression and enrichment analysis results for small cohort sizes.PLoS computational biology · 2025Article
- Liver cancer multiomics reveals diverse protein kinase A disruptions convergently produce fibrolamellar hepatocellular carcinoma.Nature communications · 2024Article
- Article
- Explainable Machine Learning Models Using Robust Cancer Biomarkers Identification from Paired Differential Gene Expression.International journal of molecular sciences · 2024Article
- WNT5A is a putative epi-driver of prostate cancer metastasis to the bone.Cancer medicine · 2024Article
- Transcriptome from Paired Samples Improves the Power of Comprehensive COVID-19 Host-Viral Characterization.International journal of molecular sciences · 2023Article
- Insights from a Computational-Based Approach for Analyzing Autophagy Genes across Human Cancers.Genes · 2023Review
- Transcriptome analysis of human peri-implant soft tissue and periodontal gingiva: a paired design study.Clinical oral investigations · 2023Article
- Inference of differentially expressed genes using generalized linear mixed models in a pairwise fashion.PeerJ · 2023Article
- Tumour microbiomes and Fusobacterium genomics in Vietnamese colorectal cancer patients.NPJ biofilms and microbiomes · 2022Article
- Global microRNA expression profile in laryngeal carcinoma unveils new prognostic biomarkers and novel insights into field cancerization.Scientific reports · 2022Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
backgroundWhen genomics researchers design a high-throughput study to test for differential expression, some biological systems and research questions provide opportunities to use paired samples from subjects, and researchers can plan for a certain proportion of subjects to have paired samples. We consider the effect of this paired samples proportion on the statistical power of the study, using characteristics of both count (RNA-Seq) and continuous (microarray) expression data from a colorectal cancer study.
resultsWe demonstrate that a higher proportion of subjects with paired samples yields higher statistical power, for various total numbers of samples, and for various strengths of subject-level confounding factors. In the design scenarios considered, the statistical power in a fully-paired design is substantially (and in many cases several times) greater than in an unpaired design.
conclusionsFor the many biological systems and research questions where paired samples are feasible and relevant, substantial statistical power gains can be achieved at the study design stage when genomics researchers plan on using paired samples from the largest possible proportion of subjects. Any cost savings in a study design with unpaired samples are likely accompanied by underpowered and possibly biased results.
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