(Q35684840)

9 August 2017

title

An automated RNA-Seq analysis pipeline to identify and visualize differentially expressed genes and pathways in CHO cells (English)

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9 August 2017

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Chun Chen

1

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9 August 2017

Huong Le

series ordinal

2

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9 August 2017

Chetan T Goudar

series ordinal

3

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9 August 2017

publication date

6 July 2015

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9 August 2017

published in

Biotechnology Progress

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9 August 2017

volume

31

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9 August 2017

issue

5

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9 August 2017

page(s)

1150-1162

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The emerging CHO systems biology era: harnessing the 'omics revolution for biotechnology

9 August 2017

cites work

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circlize Implements and enhances circular visualization in R.

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A comparison of methods for differential expression analysis of RNA-seq data

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RNA-seq differential expression studies: more sequence or more replication?

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Enriching the gene set analysis of genome-wide data by incorporating directionality of gene expression and combining statistical hypotheses and methods

21 January 2018

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A comparison of gene set analysis methods in terms of sensitivity, prioritization and specificity

21 January 2018

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

21 January 2018

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Gene set analysis methods: statistical models and methodological differences

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Comprehensive evaluation of differential gene expression analysis methods for RNA-seq data

21 January 2018

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A comparative study of techniques for differential expression analysis on RNA-Seq data

21 January 2018

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Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation

21 January 2018

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Comparison of software packages for detecting differential expression in RNA-seq studies

21 January 2018

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21 January 2018

Identifiers

DOI

10.1002/BTPR.2137

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9 August 2017

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