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

Genetic and nongenetic variation revealed for the principal components of human gene expression.

Genetics - 1 Nov 2013

Goldinger Anita, Henders Anjali K, McRae Allan F, Martin Nicholas G, Gibson Greg, Montgomery Grant W, Visscher Peter M, Powell Joseph E

Abstract excerpt

Principal components analysis has been employed in gene expression studies to correct for population substructure and batch and environmental effects. This method typically involves the removal of variation contained in as many as 50 principal components (PCs), which can constitute a large propor...

Read the complete abstract on PubMed

Topics

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

Share to Gene Expression Profiling
Share to Genetic Variation
Share to Genome-Wide Association Study

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Linear Models

Share to Models, Genetic

Share to Principal Component Analysis

Share to Quantitative Trait, Heritable

Share to Quantitative Trait Loci

Source

Open in PubMed Open full text

Identifiers

PMID: 24026092
DOI: 10.1534/genetics.113.153221
PMCID: PMC3813841

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 4 Sept 2026. Prepared record publication-24026092-2026-09-04.2. Manifest publication-graph-cohort-2026-09-04.2.

Source receipt: PubMed via Helena Literature Corpus, retrieved 4 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Genetic and nongenetic variation revealed for the principal components of human gene expression.PMID 24026092Read ↗

Unbiased identification of unknown cellular and environmental factors that mediate eQTLs using principal interaction component analysisSemantic proximity Read ↗

Principal component analysis based methods in bioinformatics studies.Semantic proximity Read ↗

Statistical significance of variables driving systematic variation in high-dimensional data.Semantic proximity Read ↗

Adjusting for principal components can induce spurious associations in genome-wide association studies in admixed populationsSemantic proximity Read ↗

Exploring pleiotropy using principal components.Semantic proximity Read ↗

A new statistic for identifying batch effects in high-throughput genomic data that uses guided principal component analysis.Semantic proximity Read ↗

Quantifying direct genetic signal captured by principal component adjustment.Semantic proximity Read ↗

Characterization of histone modification patterns and prediction of novel promoters using functional principal component analysis.Semantic proximity Read ↗

Maximizing the power of principal-component analysis of correlated phenotypes in genome-wide association studies.Semantic proximity Read ↗

Expression reflects population structureSemantic proximity Read ↗

Control of population stratification by correlation-selected principal components.Semantic proximity Read ↗

Limitations of principal components in quantitative genetic association models for human studiesSemantic proximity Read ↗

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