Using probabilistic estimation of expression residuals (PEER) to obtain increased power and interpretability of gene expression analyses
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Quantitative Trait Loci Identify Functional Noncoding Variation in CancerMT-HESS: an efficient Bayesian approach for simultaneous association detection in OMICS datasets, with application to eQTL mapping in multiple tissuesStatistical Methods in Integrative GenomicsA statistical framework for joint eQTL analysis in multiple tissuesAberrant gene expression in humansRNA Sequencing and AnalysisA gene-based association method for mapping traits using reference transcriptome dataGenome-wide association analysis of chronic lymphocytic leukaemia, Hodgkin lymphoma and multiple myeloma identifies pleiotropic risk lociGenetic Regulation of Adipose Gene Expression and Cardio-Metabolic Traits.RNA-Seq optimization with eQTL gold standards.Computational solutions for omics data.Rare and common epilepsies converge on a shared gene regulatory network providing opportunities for novel antiepileptic drug discovery.Pathway-based factor analysis of gene expression data produces highly heritable phenotypes that associate with age.quantro: a data-driven approach to guide the choice of an appropriate normalization methodTranscript Expression Data from Human Islets Links Regulatory Signals from Genome-Wide Association Studies for Type 2 Diabetes and Glycemic Traits to Their Downstream Effectors.Multi-perspective quality control of Illumina RNA sequencing data analysis.SPIRE, a modular pipeline for eQTL analysis of RNA-Seq data, reveals a regulatory hotspot controlling miRNA expression in C. elegans.Scater: pre-processing, quality control, normalization and visualization of single-cell RNA-seq data in RHuman population-specific gene expression and transcriptional network modification with polymorphic transposable elements.Joint genetic analysis using variant sets reveals polygenic gene-context interactions.Prediction of gene expression with cis-SNPs using mixed models and regularization methodsAn independent component analysis confounding factor correction framework for identifying broad impact expression quantitative trait lociExploring genetic associations with ceRNA regulation in the human genome.Clinical Genomics: Challenges and OpportunitiesEffects of Type 1 Diabetes Risk Alleles on Immune Cell Gene ExpressionDifferential expression analysis for RNAseq using Poisson mixed models.Systematic analysis of gene expression patterns associated with postmortem interval in human tissues.Joint modelling of confounding factors and prominent genetic regulators provides increased accuracy in genetical genomics studies.Transcriptome sequencing of a large human family identifies the impact of rare noncoding variantsExtent, causes, and consequences of small RNA expression variation in human adipose tissue.NOREVA: normalization and evaluation of MS-based metabolomics data.Genome-wide association study identifies multiple susceptibility loci for multiple myeloma.A genome-wide integrative study of microRNAs in human liver.Relationship of DNA methylation and gene expression in idiopathic pulmonary fibrosis.Integrative analyses of genetic variation, epigenetic regulation, and the transcriptome to elucidate the biology of platinum sensitivityConstraint and divergence of global gene expression in the mammalian embryo.Cross-population joint analysis of eQTLs: fine mapping and functional annotation.A pooling-based approach to mapping genetic variants associated with DNA methylation.Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans.Accurate and fast multiple-testing correction in eQTL studies.
P2860
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P2860
Using probabilistic estimation of expression residuals (PEER) to obtain increased power and interpretability of gene expression analyses
description
2012 nî lūn-bûn
@nan
2012 թուականի Փետրուարին հրատարակուած գիտական յօդուած
@hyw
2012 թվականի փետրվարին հրատարակված գիտական հոդված
@hy
2012年の論文
@ja
2012年論文
@yue
2012年論文
@zh-hant
2012年論文
@zh-hk
2012年論文
@zh-mo
2012年論文
@zh-tw
2012年论文
@wuu
name
Using probabilistic estimation ...... ty of gene expression analyses
@ast
Using probabilistic estimation ...... ty of gene expression analyses
@en
Using probabilistic estimation of expression residuals
@nl
type
label
Using probabilistic estimation ...... ty of gene expression analyses
@ast
Using probabilistic estimation ...... ty of gene expression analyses
@en
Using probabilistic estimation of expression residuals
@nl
prefLabel
Using probabilistic estimation ...... ty of gene expression analyses
@ast
Using probabilistic estimation ...... ty of gene expression analyses
@en
Using probabilistic estimation of expression residuals
@nl
P2860
P50
P356
P1433
P1476
Using probabilistic estimation ...... ty of gene expression analyses
@en
P2093
P2860
P2888
P304
P356
10.1038/NPROT.2011.457
P577
2012-02-16T00:00:00Z
P5875
P6179
1020020965