Deep Sequencing Data Analysis

Noam Shomron

ISBN 10: 1627035133 / ISBN 13: 9781627035132

Published by Humana Press, Humana Press Jul 2013, 2013

About this Item

Neuware -The new genetic revolution is fuelled by Deep Sequencing (or Next Generation Sequencing) apparatuses which, in essence, read billions of nucleotides per reaction. Effectively, when carefully planned, any experimental question which can be translated into reading nucleic acids can be applied.InDeep Sequencing Data Analysis,expert researchers in the field detail methods which are now commonly used to studythe multi-facet deep sequencing data field. These included techniques for compressing of data generated,Chromatin Immunoprecipitation (ChIP-seq), and various approaches for the identification of sequence variants. Written in the highly successfulMethods in Molecular Biology series format, chapters include introductions to their respective topics, lists of necessary materials and reagents, step-by-step, readily reproducible protocols, and key tips on troubleshooting and avoiding known pitfalls.Authoritative and practical,Deep Sequencing Data Analysisseeks to aid scientists in the further understanding ofkey data analysis procedures for deep sequencing data interpretation.Humana Press in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin 244 pp. Englisch.

Seller Inventory # 9781627035132

Bibliographic Details

• Title: Deep Sequencing Data Analysis
• Publisher: Humana Press, Humana Press Jul 2013
• Publication Date: 2013
• Language: English
• ISBN 10: 1627035133
• ISBN 13: 9781627035132
• Binding: Buch
• Condition: Neu

About this title

Synopsis

The new genetic revolution is fuelled by Deep Sequencing (or Next Generation Sequencing) apparatuses which, in essence, read billions of nucleotides per reaction. Effectively, when carefully planned, any experimental question which can be translated into reading nucleic acids can be applied.In Deep Sequencing Data Analysis, expert researchers in the field detail methods which are now commonly used to study the multi-facet deep sequencing data field. These included techniques for compressing of data generated, Chromatin Immunoprecipitation (ChIP-seq), and various approaches for the identification of sequence variants. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of necessary materials and reagents, step-by-step, readily reproducible protocols, and key tips on troubleshooting and avoiding known pitfalls.

 

Authoritative and practical, Deep Sequencing Data Analysis seeks to aid scientists in the further understanding of key data analysis procedures for deep sequencing data interpretation.