Network Module-Based Model in the Differential Expression Analysis for RNA-seq.

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Covariate-dependent negative binomial factor analysis of RNA sequencing data.

P2860

Q55514149-791800BF-9836-4EAB-A2EA-FF5B0F409C92

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Network Module-Based Model in the Differential Expression Analysis for RNA-seq.

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Network Module-Based Model in the Differential Expression Analysis for RNA-seq.

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Network Module-Based Model in the Differential Expression Analysis for RNA-seq.

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Network Module-Based Model in the Differential Expression Analysis for RNA-seq.

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P1476

Network Module-Based Model in the Differential Expression Analysis for RNA-seq.

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P2093

Jia Xu

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Jing Li

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

Li-Ching Huang

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Lily Wang

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Mingli Lei

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P2860

Differential expression analysis for sequence count data

Mapping and quantifying mammalian transcriptomes by RNA-Seq

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

Prostaglandin endoperoxides. Novel transformations of arachidonic acid in human platelets

RNA-seq: an assessment of technical reproducibility and comparison with gene expression arrays

A comparison of statistical methods for detecting differentially expressed genes from RNA-seq data

edgeR: a Bioconductor package for differential expression analysis of digital gene expression data

Evaluation of statistical methods for normalization and differential expression in mRNA-Seq experiments

Convergence of Wnt, beta-catenin, and cadherin pathways

GSVA: gene set variation analysis for microarray and RNA-seq data.

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scholarly article

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10.1093/BIOINFORMATICS/BTX214

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English

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2017-04-12T00:00:00Z

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28407034

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P921

RNA-Seq

RNA analysis

Network Module-Based Model in the Differential Expression Analysis for RNA-seq.

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P2860

P2860

Network Module-Based Model in the Differential Expression Analysis for RNA-seq.

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P1433

P1476

P2093

P2860

P31

P356

P407

P577

P698

P921

P356

P1433

P1476

P2093

P2860

P31

P356

P407

P577

P698

P921