Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

The PowerAtlas: a power and sample size atlas for microarray experimental design and research.

BMC bioinformatics - 22 Feb 2006

Page Grier P, Edwards Jode W, Gadbury Gary L, Yelisetti Prashanth, Wang Jelai, Trivedi Prinal, Allison David B

Abstract excerpt

BACKGROUND: Microarrays permit biologists to simultaneously measure the mRNA abundance of thousands of genes. An important issue facing investigators planning microarray experiments is how to estimate the sample size required for good statistical power. What is the projected sample size or number of replicate chips needed to address the multiple hypotheses with acceptable accuracy? Statistical methods exist for...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Data Interpretation, Statistical
Share to Databases, Genetic

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Internet

Share to Models, Statistical

Share to Probability

Share to Programming Languages

Share to Research Design

Share to Sample Size

Source

Open in PubMed Open full text

Identifiers

PMID: 16504070
DOI: 10.1186/1471-2105-7-84
PMCID: PMC1395338

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

The PowerAtlas: a power and sample size atlas for microarray experimental design and research.PMID 16504070Read ↗

Power and sample size for DNA microarray studies.Semantic proximity Read ↗

Power and sample size calculations for high-throughput sequencing-based experiments.Semantic proximity Read ↗

Split-plot microarray experiments: issues of design, power and sample size.Semantic proximity Read ↗

The power and promise of RNA-seq in ecology and evolution.Semantic proximity Read ↗

Priors, population sizes, and power in genome-wide hypothesis testsSemantic proximity Read ↗

PowerTools: A web based user-friendly tool for future translational study designSemantic proximity Read ↗

Using ANOVA to analyze microarray data.Semantic proximity Read ↗

Sample size calculation for a NanoString GeoMx spatial transcriptomics experiment to study predictors of fibrosis progression in non-alcoholic fatty liver diseaseSemantic proximity Read ↗

RMeDPower2 for Biology: guiding the design, experimental structure and analyses of experiments generating repeated measures datasetsSemantic proximity Read ↗

Working with Oligonucleotide Arrays.Semantic proximity Read ↗

Power analysis for genome-wide association studies.Semantic proximity Read ↗

Power calculator for detecting allelic imbalance using hierarchical Bayesian model.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.