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Genomic Structural Variants

Overview of attention for book
Cover of 'Genomic Structural Variants'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 What Have Studies of Genomic Disorders Taught Us About Our Genome?
  3. Altmetric Badge
    Chapter 2 Microdeletion and microduplication syndromes.
  4. Altmetric Badge
    Chapter 3 Structural Genomic Variation in Intellectual Disability
  5. Altmetric Badge
    Chapter 4 Copy Number Variation and Psychiatric Disease Risk
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    Chapter 5 Detection and characterization of copy number variation in autism spectrum disorder.
  7. Altmetric Badge
    Chapter 6 Structural Variation in Subtelomeres
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    Chapter 7 Array-Based Approaches in Prenatal Diagnosis
  9. Altmetric Badge
    Chapter 8 Structural Variation and Its Effect on Expression
  10. Altmetric Badge
    Chapter 9 The Challenges of Studying Complex and Dynamic Regions of the Human Genome
  11. Altmetric Badge
    Chapter 10 Population Genetic Nature of Copy Number Variation
  12. Altmetric Badge
    Chapter 11 Detection and interpretation of genomic structural variation in mammals.
  13. Altmetric Badge
    Chapter 12 Structural Genetic Variation in the Context of Somatic Mosaicism
  14. Altmetric Badge
    Chapter 13 Online resources for genomic structural variation.
  15. Altmetric Badge
    Chapter 14 Algorithm Implementation for CNV Discovery Using Affymetrix and Illumina SNP Array Data
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    Chapter 15 Targeted Screening and Validation of Copy Number Variations
  17. Altmetric Badge
    Chapter 16 High-Resolution Copy Number Profiling by Array CGH Using DNA Isolated from Formalin-Fixed, Paraffin-Embedded Tissues
  18. Altmetric Badge
    Chapter 17 Characterizing and Interpreting Genetic Variation from Personal Genome Sequencing
  19. Altmetric Badge
    Chapter 18 Massively Parallel Sequencing Approaches for Characterization of Structural Variation
Attention for Chapter 5: Detection and characterization of copy number variation in autism spectrum disorder.
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (94th percentile)

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Chapter title
Detection and characterization of copy number variation in autism spectrum disorder.
Chapter number 5
Book title
Genomic Structural Variants
Published in
Methods in molecular biology, January 2012
DOI 10.1007/978-1-61779-507-7_5
Pubmed ID
Book ISBNs
978-1-61779-506-0, 978-1-61779-507-7
Authors

Christian R. Marshall, Stephen W. Scherer, Marshall, Christian R., Scherer, Stephen W.

Editors

Lars Feuk

Abstract

There now exist multiple lines of evidence pointing to a significant genetic component underlying the aetiology of autism spectrum disorders (ASDs). The advent of methodologies for scanning the human genome at high resolution, coupled with the recognition of copy number variation (CNV) as a prevalent source of genomic variation, has led to new strategies in the identification of clinically relevant loci. Balanced genomic changes, such as translocations and inversions, also contribute to ASD, but current studies have shown that screening with microarrays has up to fivefold increase in diagnostic yield. Recent work by our group and others has shown unbalanced genomic alterations that are likely pathogenic in upwards of 10% of cases, highlighting an important role for CNVs in the genetic aetiology of ASD. A trend in our empirical data has shifted focus for discovery of candidate loci towards individually rare but highly penetrant CNVs instead of looking for common variants of low penetrance. This strategy has proven largely successful in identifying ASD-susceptibility candidate loci, including gains and losses at 16p11.2, SHANK2, NRXN1, and PTCHD1. Another emerging and intriguing trend is the identification of the same genes implicated by rare CNVs across neurodevelopmental disorders, including schizophrenia, attention deficit hyperactivity disorder, and intellectual disability. These observations indicate that similar pathways may be involved in phenotypically distinct outcomes. Although interrogation of the genome at high resolution has led to these novel discoveries, it has also made cataloguing, characterization, and clinical interpretation of the increasing amount of CNV data difficult. Herein, we describe the history of genomic structural variation in ASD and how CNV discovery has been used to pinpoint novel ASD-susceptibility loci. We also discuss the overlap of CNVs across neurodevelopmental disorders and comment on the current challenges of understanding the relationship between CNVs and associated phenotypes in a clinical context.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 124 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Italy 2 2%
Spain 2 2%
United Kingdom 1 <1%
China 1 <1%
Iceland 1 <1%
Unknown 117 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 28 23%
Researcher 15 12%
Student > Bachelor 13 10%
Student > Master 11 9%
Student > Doctoral Student 8 6%
Other 23 19%
Unknown 26 21%
Readers by discipline Count As %
Agricultural and Biological Sciences 21 17%
Biochemistry, Genetics and Molecular Biology 18 15%
Medicine and Dentistry 14 11%
Psychology 10 8%
Neuroscience 8 6%
Other 23 19%
Unknown 30 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 15. 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 27 December 2023.
All research outputs
#2,370,373
of 25,066,230 outputs
Outputs from Methods in molecular biology
#381
of 14,097 outputs
Outputs of similar age
#17,497
of 255,809 outputs
Outputs of similar age from Methods in molecular biology
#30
of 491 outputs
Altmetric has tracked 25,066,230 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 14,097 research outputs from this source. They receive a mean Attention Score of 3.5. This one has done particularly well, scoring higher than 97% of its peers.
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We're also able to compare this research output to 491 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 94% of its contemporaries.