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Copy Number Variants

Overview of attention for book
Cover of 'Copy Number Variants'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Identification of Copy Number Variants from SNP Arrays Using PennCNV
  3. Altmetric Badge
    Chapter 2 Using SAAS-CNV to Detect and Characterize Somatic Copy Number Alterations in Cancer Genomes from Next Generation Sequencing and SNP Array Data
  4. Altmetric Badge
    Chapter 3 Statistical Detection of Genome Differences Based on CNV Segments
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    Chapter 4 Whole-Genome Shotgun Sequence CNV Detection Using Read Depth
  6. Altmetric Badge
    Chapter 5 Read Depth Analysis to Identify CNV in Bacteria Using CNOGpro
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    Chapter 6 Using HaMMLET for Bayesian Segmentation of WGS Read-Depth Data
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    Chapter 7 Split-Read Indel and Structural Variant Calling Using PINDEL
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    Chapter 8 Detecting Small Inversions Using SRinversion
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    Chapter 9 Detection of CNVs in NGS Data Using VS-CNV
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    Chapter 10 Structural Variant Breakpoint Detection with novoBreak
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    Chapter 11 Use of RAPTR-SV to Identify SVs from Read Pairing and Split Read Signatures
  13. Altmetric Badge
    Chapter 12 Versatile Identification of Copy Number Variants with Canvas
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    Chapter 13 A Randomized Iterative Approach for SV Discovery with SVelter
  15. Altmetric Badge
    Chapter 14 Analysis of Population-Genetic Properties of Copy Number Variations
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    Chapter 15 Validation of Genomic Structural Variants Through Long Sequencing Technologies
  17. Altmetric Badge
    Chapter 16 Structural Variation Detection and Analysis Using Bionano Optical Mapping
Attention for Chapter 2: Using SAAS-CNV to Detect and Characterize Somatic Copy Number Alterations in Cancer Genomes from Next Generation Sequencing and SNP Array Data
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Chapter title
Using SAAS-CNV to Detect and Characterize Somatic Copy Number Alterations in Cancer Genomes from Next Generation Sequencing and SNP Array Data
Chapter number 2
Book title
Copy Number Variants
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-8666-8_2
Pubmed ID
30039361
Book ISBNs
978-1-4939-8665-1, 978-1-4939-8666-8
Authors

Zhongyang Zhang, Ke Hao, Zhang, Zhongyang, Hao, Ke

Abstract

Somatic copy number alterations (SCNAs) are profound in cancer genomes at different stages: oncogenesis, progression, and metastasis. Accurate detection and characterization of SCNA landscape at genome-wide scale are of great importance. Next-generation sequencing and SNP array are current technology of choice for SCNA analysis. They are able to quantify SCNA with high resolution and meanwhile raise great challenges in data analysis. To this end, we have developed an R package saasCNV for SCNA analysis using (1) whole-genome sequencing (WGS), (2) whole-exome sequencing (WES) or (3) whole-genome SNP array data. In this chapter, we provide the features of the package and step-by-step instructions in detail.

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X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
 Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 22%
Professor 1 11%
Student > Bachelor 1 11%
Other 1 11%
Unknown 4 44%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 2 22%
Computer Science 1 11%
Agricultural and Biological Sciences 1 11%
Immunology and Microbiology 1 11%
Unknown 4 44%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 25 July 2018.
All research outputs
#20,527,576
of 23,096,849 outputs
Outputs from Methods in molecular biology
#9,977
of 13,208 outputs
Outputs of similar age
#378,510
of 442,670 outputs
Outputs of similar age from Methods in molecular biology
#1,194
of 1,499 outputs
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So far Altmetric has tracked 13,208 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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