ArticleNature protocols2012
Using probabilistic estimation of expression residuals (PEER) to obtain increased power and interpretability of gene expression analyses.
Article in Nature protocols, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 654 papers, 6 of them syntheses that pooled it.
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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.
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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
654 citing papers in PubMed, 6 syntheses or guidelines pooled it.
- eQTL Meta-Analysis Reveals Conserved and Population-Specific Regulatory Variation Underlying Nutritional Trait Evolution and Domestication in Tomato.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Pooled it
- Integrative genetic and liver transcriptomic analyses identify TRIB1AL as a target for steatotic liver disease.The Journal of clinical endocrinology and metabolism · 2026Pooled it
- A practical guide to identifying associations between tandem repeats and complex human traits using consensus genotypes from multiple tools.Nature protocols · 2026Guideline
- Skeletal muscle eQTL meta-analysis implicates genes in the genetic architecture of muscular and cardiometabolic traits.American journal of human genetics · 2025Pooled it
- Adipose tissue eQTL meta-analysis highlights the contribution of allelic heterogeneity to gene expression regulation and cardiometabolic traits.Nature genetics · 2025Pooled it
- GWAS meta-analysis reveals key risk loci in essential tremor pathogenesis.Communications biology · 2024Pooled it
- DNA detection using metal-enhanced fluorescence.RSC advances · 2026Article
- Genotype-driven variations in lncRNA expression underlie predisposition to high-grade serous ovarian cancer.Journal of advanced research · 2026Article
- Single-cell profiling and genetic regulation of alternative polyadenylation in the human brain.Nature genetics · 2026Article
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- Identifying causal genetic variants for high-altitude adaptation through blood eQTL analysis in plateau populations.Communications biology · 2026Article
- Alternative tandem transcription initiation links noncoding variants to human disease through translational control.Nature communications · 2026Article
- The genetic architecture of fibromyalgia across 2.5 million individuals.Nature medicine · 2026Article
- Integrated Genomic and Transcriptomic Study RevealsCirculation. Genomic and precision medicine · 2026Article
- Integrative Multi-Omics Analysis Reveals the Genetic Architecture Landscape of the Blood Metabolome in Jersey Cattle.Animals : an open access journal from MDPI · 2026Article
- Atlas of glomerular disease-specific genetic effects on blood transcriptome.medRxiv : the preprint server for health sciences · 2026Article
- Integrating single-cell sQTL mapping with deep-learning splicing prediction identifies causal variants under influenza infection.Genome biology · 2026Article
- Independent component analysis deciphers the genetic basis of cotton fiber elongation through eQTLs and sQTLs.Journal of advanced research · 2026Article
- Integrated DNA methylome and transcriptome signatures of lung CD4ERJ open research · 2026Article
594 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
We present PEER (probabilistic estimation of expression residuals), a software package implementing statistical models that improve the sensitivity and interpretability of genetic associations in population-scale expression data. This approach builds on factor analysis methods that infer broad variance components in the measurements. PEER takes as input transcript profiles and covariates from a set of individuals, and then outputs hidden factors that explain much of the expression variability. Optionally, these factors can be interpreted as pathway or transcription factor activations by providing prior information about which genes are involved in the pathway or targeted by the factor. The inferred factors are used in genetic association analyses. First, they are treated as additional covariates, and are included in the model to increase detection power for mapping expression traits. Second, they are analyzed as phenotypes themselves to understand the causes of global expression variability. PEER extends previous related surrogate variable models and can be implemented within hours on a desktop computer.
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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.