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ROAST: rotation gene set tests for complex microarray experiments

ROAST: rotation gene set tests for complex microarray experiments

http://www.wikidata.org/entity/Q34070746

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Detection of simultaneous group effects in microRNA expression and related target gene sets The promise of multi-omics and clinical data integration to identify and target personalized healthcare approaches in autism spectrum disorders Brg1 loss attenuates aberrant wnt-signalling and prevents wnt-dependent tumourigenesis in the murine small intestine Gene Expression and MicroRNA Expression Analysis in Small Arteries of Spontaneously Hypertensive Rats. Evidence for ER Stress Early downregulation of Mcl-1 regulates apoptosis triggered by cardiac glycoside UNBS1450 XBP1-Independent UPR Pathways Suppress C/EBP-β Mediated Chondrocyte Differentiation in ER-Stress Related Skeletal Disease Proteomic and metabolomic analyses of mitochondrial complex I-deficient mouse model generated by spontaneous B2 short interspersed nuclear element (SINE) insertion into NADH dehydrogenase (ubiquinone) Fe-S protein 4 (Ndufs4) gene Hobit and Blimp1 instruct a universal transcriptional program of tissue residency in lymphocytes Transcriptional profiling of human brain endothelial cells reveals key properties crucial for predictive in vitro blood-brain barrier models Lung Basal Stem Cells Rapidly Repair DNA Damage Using the Error-Prone Nonhomologous End-Joining Pathway Cardiolipin Supports Respiratory Enzymes in Plants in Different Ways limma powers differential expression analyses for RNA-sequencing and microarray studies GSVA: gene set variation analysis for microarray and RNA-seq data.A decision-theory approach to interpretable set analysis for high-dimensional data Gene-expression data integration to squamous cell lung cancer subtypes reveals drug sensitivity Guide: a desktop application for analysing gene expression data ChIP-Enrich: gene set enrichment testing for ChIP-seq data Rotation gene set testing for longitudinal expression data.Comparative evaluation of gene set analysis approaches for RNA-Seq data.Inferring pathway dysregulation in cancers from multiple types of omic data.Pathway analysis for RNA-Seq data using a score-based approach.Gene set analysis approaches for RNA-seq data: performance evaluation and application guideline Turning publicly available gene expression data into discoveries using gene set context analysis.Metabolite profiles reveal energy failure and impaired beta-oxidation in liver of mice with complex III deficiency due to a BCS1L mutation.Poplar wood rays are involved in seasonal remodeling of tree physiology.A transcriptomics data-driven gene space accurately predicts liver cytopathology and drug-induced liver injury Control of reproductive floral organ identity specification in Arabidopsis by the C function regulator AGAMOUS.A chloroplast retrograde signal, 3'-phosphoadenosine 5'-phosphate, acts as a secondary messenger in abscisic acid signaling in stomatal closure and germination.Combining multiple tools outperforms individual methods in gene set enrichment analyses voom: Precision weights unlock linear model analysis tools for RNA-seq read counts.Pax5 loss imposes a reversible differentiation block in B-progenitor acute lymphoblastic leukemia.A knowledge-based T2-statistic to perform pathway analysis for quantitative proteomic data.A new analysis approach of epidermal growth factor receptor pathway activation patterns provides insights into cetuximab resistance mechanisms in head and neck cancer Centrality-based pathway enrichment: a systematic approach for finding significant pathways dominated by key genes The limitations of simple gene set enrichment analysis assuming gene independence.DiffVar: a new method for detecting differential variability with application to methylation in cancer and aging.Differential expression analysis for pathways.A new approach for the study of lung smooth muscle phenotypes and its application in a murine model of allergic airway inflammation.An Endotoxin Tolerance Signature Predicts Sepsis and Organ Dysfunction at Initial Clinical Presentation Left atrial transcriptional changes associated with atrial fibrillation susceptibility and persistence

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ROAST: rotation gene set tests for complex microarray experiments

http://www.wikidata.org/entity/Q34070746

description

2010 nî lūn-bûn

@nan

2010 թուականի Յուլիսին հրատարակուած գիտական յօդուած

@hyw

2010 թվականի հուլիսին հրատարակված գիտական հոդված

@hy

2010年の論文

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2010年論文

@yue

2010年論文

@zh-hant

2010年論文

@zh-hk

2010年論文

@zh-mo

2010年論文

@zh-tw

2010年论文

@wuu

name

ROAST: rotation gene set tests for complex microarray experiments

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ROAST: rotation gene set tests for complex microarray experiments

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ROAST: rotation gene set tests for complex microarray experiments

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type

label

ROAST: rotation gene set tests for complex microarray experiments

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ROAST: rotation gene set tests for complex microarray experiments

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ROAST: rotation gene set tests for complex microarray experiments

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prefLabel

ROAST: rotation gene set tests for complex microarray experiments

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ROAST: rotation gene set tests for complex microarray experiments

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ROAST: rotation gene set tests for complex microarray experiments

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ROAST: rotation gene set tests for complex microarray experiments

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Di Wu

http://www.w3.org/2001/XMLSchema#string

Elgene Lim

http://www.w3.org/2001/XMLSchema#string

François Vaillant

http://www.w3.org/2001/XMLSchema#string

Jane E Visvader

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Marie-Liesse Asselin-Labat

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P2860

Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles.

Linear models and empirical bayes methods for assessing differential expression in microarray experiments

PGC-1alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes

Improving gene set analysis of microarray data by SAM-GS.

Empirical array quality weights in the analysis of microarray data

Analyzing gene expression data in terms of gene sets: methodological issues.

Pathway analysis of microarray data via regression.

Microarray analysis after RNA amplification can detect pronounced differences in gene expression using limma

An integrated approach for the analysis of biological pathways using mixed models

Comparison of small n statistical tests of differential expression applied to microarrays.

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2176-2182

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10.1093/BIOINFORMATICS/BTQ401

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17

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26

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45101502

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20610611

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2922896

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