Rna-Seq Data Analysis : A Practical Approach

Eija Korpelainen

ISBN 10: 1466595000 / ISBN 13: 9781466595002

Published by CRC Press Sep 2014, 2014

About this Item

Neuware - The State of the Art in Transcriptome Analysis RNA sequencing (RNA-seq) data offers unprecedented information about the transcriptome, but harnessing this information with bioinformatics tools is typically a bottleneck. RNA-seq Data Analysis: A Practical Approach enables researchers to examine differential expression at gene, exon, and transcript levels and to discover novel genes, transcripts, and whole transcriptomes.

Seller Inventory # 9781466595002

Bibliographic Details

• Title: Rna-Seq Data Analysis : A Practical Approach
• Publisher: CRC Press Sep 2014
• Publication Date: 2014
• Language: English
• ISBN 10: 1466595000
• ISBN 13: 9781466595002
• Binding: Buch
• Condition: Neu
• Dimensions: 241W x 156H x 2D millimeters 241 millimeters width by 156 millimeters height by 2 millimeters depth
• Weight: 586 grams

About this title

Synopsis

The State of the Art in Transcriptome Analysis RNA sequencing (RNA-seq) data offers unprecedented information about the transcriptome, but harnessing this information with bioinformatics tools is typically a bottleneck. RNA-seq Data Analysis: A Practical Approach enables researchers to examine differential expression at gene, exon, and transcript levels and to discover novel genes, transcripts, and whole transcriptomes.

Balanced Coverage of Theory and Practice.Each chapter starts with theoretical background, followed by descriptions of relevant analysis tools and practical examples. Accessible to both bioinformaticians and nonprogramming wet lab scientists, the examples illustrate the use of command-line tools, R, and other open source tools, such as the graphical Chipster software.

The Tools and Methods to Get Started in Your Lab. Taking readers through the whole data analysis workflow, this self-contained guide provides a detailed overview of the main RNA-seq data analysis methods and explains how to use them in practice. It is suitable for researchers from a wide variety of backgrounds, including biology, medicine, genetics, and computer science. The book can also be used in a graduate or advanced undergraduate course.

About the Author

Eija Korpelainen, Jarno Tuimala, Panu Somervuo, Mikael Huss, Garry Wong