Chapter title |
A Bioinformatics Pipeline for the Identification of CHO Cell Differential Gene Expression from RNA-Seq Data
|
---|---|
Chapter number | 11 |
Book title |
Heterologous Protein Production in CHO Cells
|
Published in |
Methods in molecular biology, May 2017
|
DOI | 10.1007/978-1-4939-6972-2_11 |
Pubmed ID | |
Book ISBNs |
978-1-4939-6971-5, 978-1-4939-6972-2
|
Authors |
Monger, Craig, Motheramgari, Krishna, McSharry, John, Barron, Niall, Clarke, Colin, Craig Monger, Krishna Motheramgari, John McSharry, Niall Barron, Colin Clarke |
Editors |
Paula Meleady |
Abstract |
In recent years, the publication of genome sequences for the Chinese hamster and Chinese hamster ovary (CHO) cell lines has facilitated study of these biopharmaceutical cell factories with unprecedented resolution. Our understanding of the CHO cell transcriptome, in particular, has rapidly advanced through the application of next-generation sequencing (NGS) technology to characterize RNA expression (RNA-Seq). In this chapter, we present a computational pipeline for the analysis of CHO cell RNA-Seq data from the Illumina platform to identify differentially expressed genes. The example data and bioinformatics workflow required to run this analysis are freely available at www.cgcdb.org/rnaseq_analysis_protocol.html . |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Canada | 1 | 13% |
France | 1 | 13% |
Unknown | 6 | 75% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 5 | 63% |
Scientists | 3 | 38% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Denmark | 1 | 3% |
Unknown | 35 | 97% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 8 | 22% |
Student > Ph. D. Student | 6 | 17% |
Student > Bachelor | 5 | 14% |
Student > Master | 3 | 8% |
Student > Doctoral Student | 2 | 6% |
Other | 5 | 14% |
Unknown | 7 | 19% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 15 | 42% |
Agricultural and Biological Sciences | 3 | 8% |
Social Sciences | 2 | 6% |
Computer Science | 2 | 6% |
Pharmacology, Toxicology and Pharmaceutical Science | 1 | 3% |
Other | 3 | 8% |
Unknown | 10 | 28% |