Gene set analysis methods: statistical models and methodological differences.
about
Establishing an analytic pipeline for genome-wide DNA methylationAnalyzing and interpreting genome data at the network level with ConsensusPathDBDifferential RNA-seq, Multi-Network Analysis and Metabolic Regulation Analysis of Kluyveromyces marxianus Reveals a Compartmentalised Response to XyloseTime-Course Gene Set Analysis for Longitudinal Gene Expression DataIntegrative gene set analysis of multi-platform data with sample heterogeneity.Concordant integrative gene set enrichment analysis of multiple large-scale two-sample expression data sets.Gene set analysis approaches for RNA-seq data: performance evaluation and application guidelinehtsint: a Python library for sequencing pipelines that combines data through gene set generation.An efficient concordant integrative analysis of multiple large-scale two-sample expression data sets.Combining multiple tools outperforms individual methods in gene set enrichment analysesRanking metrics in gene set enrichment analysis: do they matter?Integrated pathway-based approach identifies association between genomic regions at CTCF and CACNB2 and schizophrenia.Multiple Trait Covariance Association Test Identifies Gene Ontology Categories Associated with Chill Coma Recovery Time in Drosophila melanogaster.Learning dysregulated pathways in cancers from differential variability analysis.A comparison of gene set analysis methods in terms of sensitivity, prioritization and specificity.EDDY: a novel statistical gene set test method to detect differential genetic dependencies.Multiset Statistics for Gene Set Analysis.An automated RNA-Seq analysis pipeline to identify and visualize differentially expressed genes and pathways in CHO cells.Quantitative gene set analysis generalized for repeated measures, confounder adjustment, and continuous covariatesComparative study on gene set and pathway topology-based enrichment methods.Integrative enrichment analysis: a new computational method to detect dysregulated pathways in heterogeneous samples.Gene set analysis using sufficient dimension reduction.A Joint Location-Scale Test Improves Power to Detect Associated SNPs, Gene Sets, and PathwaysInterpreting transcriptional changes using causal graphs: new methods and their practical utility on public networks.MinePath: Mining for Phenotype Differential Sub-paths in Molecular Pathways.Robust multi-group gene set analysis with few replicates.Detecting discordance enrichment among a series of two-sample genome-wide expression data sets.Brain Transcriptomic Response to Social Eavesdropping in Zebrafish (Danio rerio).Bioinformatics approaches for the functional interpretation of protein lists: from ontology term enrichment to network analysis.Multiple Testing of Gene Sets from Gene Ontology: Possibilities and Pitfalls.Extracting the Strongest Signals from Omics Data: Differentially Expressed Pathways and Beyond.The epigenetic modifier Fam208a is required to maintain epiblast cell fitness.Microarray profiling of preselected CHO host cell subclones identifies gene expression patterns associated with increased production capacity.GWAS summary-based pathway analysis correcting for the genetic confounding impact of environmental exposures.Databases and tools for constructing signal transduction networks in cancer.Importance of collection in gene set enrichment analysis of drug response in cancer cell lines.Tissue-specific pathway association analysis using genome-wide association study summaries.A strategy for evaluating pathway analysis methods.Integrative analysis of GWAS, eQTLs and meQTLs data suggests that multiple gene sets are associated with bone mineral density.A microRNA-mRNA expression network during oral siphon regeneration in Ciona.
P2860
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P2860
Gene set analysis methods: statistical models and methodological differences.
description
2014 nî lūn-bûn
@nan
2014 թուականի Յուլիսին հրատարակուած գիտական յօդուած
@hyw
2014 թվականի հուլիսին հրատարակված գիտական հոդված
@hy
2014年の論文
@ja
2014年論文
@yue
2014年論文
@zh-hant
2014年論文
@zh-hk
2014年論文
@zh-mo
2014年論文
@zh-tw
2014年论文
@wuu
name
Gene set analysis methods: statistical models and methodological differences.
@ast
Gene set analysis methods: statistical models and methodological differences.
@en
type
label
Gene set analysis methods: statistical models and methodological differences.
@ast
Gene set analysis methods: statistical models and methodological differences.
@en
prefLabel
Gene set analysis methods: statistical models and methodological differences.
@ast
Gene set analysis methods: statistical models and methodological differences.
@en
P2860
P356
P1476
Gene set analysis methods: statistical models and methodological differences.
@en
P2093
Henryk Maciejewski
P2860
P304
P356
10.1093/BIB/BBT002
P577
2014-07-01T00:00:00Z