ArticleJournal of computational biology : a journal of computational molecular cell biology2013
Calculating sample size estimates for RNA sequencing data.
Article in Journal of computational biology : a journal of computational molecular cell biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06385236 (Leveraging Pharmacogenomics in Asthma for Predication, Mechanism and Endotyping), which is not on this map. Cited by 200 papers, 2 of them syntheses that pooled it.
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.
Leveraging Pharmacogenomics in Asthma for Predication, Mechanism and Endotyping
Who cites it
200 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- NMN supplementation as a strategy to improve oocyte quality: a systematic review and transcriptomic analysis.Journal of assisted reproduction and genetics · 2026Pooled it
- RNA-Sequencing in Elucidating Immune Responses to Haemonchus contortus Infection in Small Ruminants: Systematic Review.Parasite immunology · 2025Pooled it
- The Vacc-SeqQC project: Benchmarking RNA-Seq for clinical vaccine studies.Frontiers in immunology · 2022Trial
- Post-operative atrial fibrillation examined using whole-genome RNA sequencing in human left atrial tissue.BMC medical genomics · 2017Trial
- Guidelines to Study Transcriptome Remodeling by Proteins Using Deep Sequencing (RNA-Seq).Methods in molecular biology (Clifton, N.J.) · 2027Article
- Transcriptomic Landscape Reveals Immunity Related Trade-Offs in an Invertebrate-Fungal Host-Parasite System.Molecular ecology · 2026Article
- Differential Expression of MicroRNAs in the Mammary Gland of Lactating and Dry Murciano-Granadina Goats.Animals : an open access journal from MDPI · 2026Article
- Skeletal muscle reprogramming of metabolic, ribosomal and developmental pathways contributes to Roux-en-Y gastric bypass-induced adaptation in women.EBioMedicine · 2026Article
- Normal spermatogenesis in older men is associated with compensatory transcriptome changes.GeroScience · 2026Article
- Arterial Tissue Gene Expression Associated With Telomere Length Attrition in Coronary Artery Disease.Journal of lipid and atherosclerosis · 2026Article
- The Utility of a Three-gene Host Response to Discriminate Tuberculous Meningitis From Other Infections in Children.The Pediatric infectious disease journal · 2026Article
- NCOR1 and NCOR2 Exhibit Distinct Cellular and Transcriptomic Signatures in Human Abdominal Aortic Aneurysm.Biomedicines · 2026Article
- Single-cell and spatial profiling in cancer biology and clinical oncology.Nature cancer · 2026Review
- Adenosine-to-inosine editing of miR-200b-3p is associated with the progression of high-grade serous ovarian cancer.Molecular oncology · 2026Article
- Sample size requirements for machine learning classification of binary outcomes in bulk RNA-Seq data.BMC bioinformatics · 2026Article
- Transcriptomic profiling of a commensal Escherichia coli lysogen in simulated intestinal fluid reveals broad changes in both core and accessory regions of the genome.BMC genomics · 2026Article
- Article
- Peripheral leukocyte transcriptomic changes in preweaned Holstein heifer calves with varying stages of Bovine Respiratory Disease.PloS one · 2026Article
- Study protocol: analysis of gene expression profiles in peripheral blood and tumor tissue of Colombian patients diagnosed with epithelial ovarian cancer.Frontiers in oncology · 2026Article
- Article
140 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
5 authors.
Funding
Abstract
backgroundGiven the high technical reproducibility and orders of magnitude greater resolution than microarrays, next-generation sequencing of mRNA (RNA-Seq) is quickly becoming the de facto standard for measuring levels of gene expression in biological experiments. Two important questions must be taken into consideration when designing a particular experiment, namely, 1) how deep does one need to sequence? and, 2) how many biological replicates are necessary to observe a significant change in expression?
resultsBased on the gene expression distributions from 127 RNA-Seq experiments, we find evidence that 91% ± 4% of all annotated genes are sequenced at a frequency of 0.1 times per million bases mapped, regardless of sample source. Based on this observation, and combining this information with other parameters such as biological variation and technical variation that we empirically estimate from our large datasets, we developed a model to estimate the statistical power needed to identify differentially expressed genes from RNA-Seq experiments.
conclusionsOur results provide a needed reference for ensuring RNA-Seq gene expression studies are conducted with the optimally sample size, power, and sequencing depth. We also make available both R code and an Excel worksheet for investigators to calculate for their own experiments.
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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.