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Deep Sequencing Data Analysis

Overview of attention for book
Cover of 'Deep Sequencing Data Analysis'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 An Introduction to High-Throughput Sequencing Experiments: Design and Bioinformatics Analysis
  3. Altmetric Badge
    Chapter 2 Compressing Resequencing Data with GReEn
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    Chapter 3 On the Accuracy of Short Read Mapping
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    Chapter 4 Statistical Modeling of Coverage in High-Throughput Data
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    Chapter 5 Assembly Algorithms for Deep Sequencing Data: Basics and Pitfalls
  7. Altmetric Badge
    Chapter 6 Short Read Mapping for Exome Sequencing
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    Chapter 7 Profiling Short Tandem Repeats from Short Reads
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    Chapter 8 Exome sequencing analysis: a guide to disease variant detection.
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    Chapter 9 Identifying RNA Editing Sites in miRNAs by Deep Sequencing
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    Chapter 10 Identifying Differential Alternative Splicing Events from RNA Sequencing Data Using RNASeq-MATS.
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    Chapter 11 Optimizing Detection of Transcription Factor-Binding Sites in ChIP-seq Experiments
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    Chapter 12 Statistical Analysis of ChIP-seq Data with MOSAiCS
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    Chapter 13 Detection of Reverse Transcriptase Termination Sites Using cDNA Ligation and Massive Parallel Sequencing
Attention for Chapter 12: Statistical Analysis of ChIP-seq Data with MOSAiCS
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Chapter title
Statistical Analysis of ChIP-seq Data with MOSAiCS
Chapter number 12
Book title
Deep Sequencing Data Analysis
Published in
Methods in molecular biology, January 2013
DOI 10.1007/978-1-62703-514-9_12
Pubmed ID
23872977
Book ISBNs
978-1-62703-513-2, 978-1-62703-514-9
Authors

Guannan Sun, Dongjun Chung, Kun Liang, Sündüz Keleş, Sun, Guannan, Chung, Dongjun, Liang, Kun, Keleş, Sündüz

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 21 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 33%
Researcher 4 19%
Other 3 14%
Professor 2 10%
Student > Doctoral Student 2 10%
Other 0 0%
Unknown 3 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 9 43%
Biochemistry, Genetics and Molecular Biology 5 24%
Mathematics 2 10%
Computer Science 1 5%
Social Sciences 1 5%
Other 0 0%
Unknown 3 14%

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