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Cancer Gene Profiling

Overview of attention for book
Attention for Chapter 13: Reproducible, Scalable Fusion Gene Detection from RNA-Seq.
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Chapter title
Reproducible, Scalable Fusion Gene Detection from RNA-Seq.
Chapter number 13
Book title
Cancer Gene Profiling
Published in
Methods in molecular biology, January 2016
DOI 10.1007/978-1-4939-3204-7_13
Pubmed ID
Book ISBNs
978-1-4939-3203-0, 978-1-4939-3204-7
Authors

Vladan Arsenijevic, Brandi N. Davis-Dusenbery

Editors

Robert Grützmann, Christian Pilarsky

Abstract

Chromosomal rearrangements resulting in the creation of novel gene products, termed fusion genes, have been identified as driving events in the development of multiple types of cancer. As these gene products typically do not exist in normal cells, they represent valuable prognostic and therapeutic targets. Advances in next-generation sequencing and computational approaches have greatly improved our ability to detect and identify fusion genes. Nevertheless, these approaches require significant computational resources. Here we describe an approach which leverages cloud computing technologies to perform fusion gene detection from RNA sequencing data at any scale. We additionally highlight methods to enhance reproducibility of bioinformatics analyses which may be applied to any next-generation sequencing experiment.

Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 40%
Researcher 1 20%
Student > Master 1 20%
Unknown 1 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 2 40%
Computer Science 1 20%
Medicine and Dentistry 1 20%
Unknown 1 20%