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Title Deep sequencing data analysis / edited by Noam Shomron
Published New York : Humana Press, ©2013


Description 1 online resource (x, 234 pages) : illustrations (some color)
Series Methods in molecular biology, 1940-6029 ; 1038
Methods in molecular biology (Clifton, N.J.) ; v. 1038. 1064-3745
Contents Introduction to high-throughput sequencing experiments : design and bioinformatics analysis / Rachelly Normand and Itai Yanai -- Compressing resequencing data with GReEn / Armando J. Pinho, Diogo Pratas, and Sara P. Garcia -- On the accuracy of short read mapping / Peter Menzel [and others] -- Statistical modeling of coverage in high-throughput data / David Golan and Saharon Rosset -- Assembly algorithms for deep sequencing data : basics and pitfalls / Nitzan Kol and Noam Shomron -- Short read mapping for exome sequencing / Xueya Zhou [and others] -- Profiling short tandem repeats from short reads / Melissa Gymrek and Yaniv Erlich -- Exome sequencing analysis : a guide to disease variant detection / Ofer Isakov, Marie Perrone, and Noam Shomron -- Identifying RNA editing sites in miRNAs by deep sequencing / Shahar Alon and Eli Eisenberg -- Identifying differential alternative splicing events from RNA sequencing data using RNASeq-MATS / Juw Won Park [and others] -- Optimizing detection of transcription factor-binding sites in ChIP-seq experiments / Aleksi Kallio and Laura L. Elo -- Statistical analysis of ChIP-seq data with MOSAiCS / Guannan Sun [and others] -- Detection of reverse transcriptase termination sites using cDNA ligation and massive parallel sequencing / Lukasz J. Kielpinski [and others]
Summary 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
Analysis Life sciences
Human genetics
dna sequencing
humane genetica
Genetics (General)
Genetica (algemeen)
Bibliography Includes bibliographical references and index
Notes English
Online resource; title from PDF title page (SpringerLink, viewed July 31, 2013)
Subject Nucleotide sequence -- Laboratory manuals
Nucleotide sequence -- Data processing -- Laboratory manuals
Decision making -- Mathematical models.
Genetics -- Technique.
Sequence Analysis
Decision Support Techniques
Genetic Techniques
Investigative Techniques
Analytical, Diagnostic and Therapeutic Techniques and Equipment
Data Interpretation, Statistical
High-Throughput Nucleotide Sequencing
Genetics -- Technique
Decision making -- Mathematical models
Nucleotide sequence
Nucleotide sequence -- Data processing
Genre/Form Laboratory manuals
Laboratory manuals.
Manuels de laboratoire.
Form Electronic book
Author Shomron, Noam
ISBN 9781627035149