Deep sequencing data analysis / edited by Noam Shomron.

Contributor(s): Shomron, Noam
Material type: TextTextSeries: Methods in molecular biology (Clifton, N.J.): v. 1038.Publisher: New York : Humana Press, ©2013Description: 1 online resource (x, 234 pages) : illustrations (some color)Content type: text Media type: computer Carrier type: online resourceISBN: 9781627035149; 1627035141; 1627035133; 9781627035132Subject(s): Nucleotide sequence -- Laboratory manuals | Nucleotide sequence -- Data processing -- Laboratory manuals | Sequence Analysis | Decision Support Techniques | Genetic Techniques | Investigative Techniques | Analytical, Diagnostic and Therapeutic Techniques and Equipment | Data Interpretation, Statistical | High-Throughput Nucleotide Sequencing | Nucleotide sequence | Nucleotide sequence -- Data processing | Life sciences | Human genetics | Bioinformatics | dna sequencing | humane genetica | Genetics (General) | Genetica (algemeen)Genre/Form: Electronic books. | Laboratory manuals. Additional physical formats: Printed edition:: No titleDDC classification: 572.8/633 LOC classification: QP625.N89 | D44 2013Online resources: Click here to access online
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.
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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].

Includes bibliographical references and index.

Online resource; title from PDF title page (SpringerLink, viewed July 31, 2013).

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.

English.

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