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Whole Genome Amplification

Overview of attention for book
Cover of 'Whole Genome Amplification'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Principles of Whole-Genome Amplification
  3. Altmetric Badge
    Chapter 2 Bias in Whole Genome Amplification: Causes and Considerations.
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    Chapter 3 The Single-Cell Lab or How to Perform Single-Cell Molecular Analysis
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    Chapter 4 Sample Preparation Methods Following CellSearch Approach Compatible of Single-Cell Whole-Genome Amplification: An Overview
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    Chapter 5 Deterministic Whole-Genome Amplification of Single Cells.
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    Chapter 6 Construction of a DNA Library on Microbeads Using Whole Genome Amplification
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    Chapter 7 Heat-Induced Fragmentation and Adapter-Assisted Whole Genome Amplification Using GenomePlex ® Single-Cell Whole Genome Amplification Kit (WGA4)
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    Chapter 8 Whole Genome Amplification by Isothermal Multiple Strand Displacement Using Phi29 DNA Polymerase.
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    Chapter 9 Using Multiplex PCR for Assessing the Quality of Whole Genome Amplified DNA
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    Chapter 10 Quality Control of Isothermal Amplified DNA Based on Short Tandem Repeat Analysis
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    Chapter 11 Laser Microdissection of FFPE Tissue Areas and Subsequent Whole Genome Amplification by Ampli 1™
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    Chapter 12 Whole Genome Amplification from Blood Spot Samples
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    Chapter 13 Analysis of Whole Mitogenomes from Ancient Samples
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    Chapter 14 Copy Number Variation Analysis by Array Analysis of Single Cells Following Whole Genome Amplification.
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    Chapter 15 Whole Genome Amplification in Genomic Analysis of Single Circulating Tumor Cells.
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    Chapter 16 Whole Genome Amplification of Labeled Viable Single Cells Suited for Array-Comparative Genomic Hybridization
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    Chapter 17 Low-Volume On-Chip Single-Cell Whole Genome Amplification for Multiple Subsequent Analyses.
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    Chapter 18 Detection and Characterization of Circulating Tumor Cells by the CellSearch Approach
Attention for Chapter 2: Bias in Whole Genome Amplification: Causes and Considerations.
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About this Attention Score

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  • High Attention Score compared to outputs of the same age and source (84th percentile)

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Chapter title
Bias in Whole Genome Amplification: Causes and Considerations.
Chapter number 2
Book title
Whole Genome Amplification
Published in
Methods in molecular biology, January 2015
DOI 10.1007/978-1-4939-2990-0_2
Pubmed ID
Book ISBNs
978-1-4939-2989-4, 978-1-4939-2990-0
Authors

Sabina, Jeffrey, Leamon, John H, Jeffrey Sabina, John H. Leamon, Leamon, John H.

Abstract

Whole genome amplification (WGA) is a widely used molecular technique that is becoming increasingly necessary in genetic research on a range of sample types including individual cells, fossilized remains and entire ecosystems. Multiple methods of WGA have been developed, each with specific strengths and weaknesses, but with a common defect in that each method distorts the initial template DNA during the course of amplification. The type, extent, and circumstance of the bias vary with the WGA method and particulars of the template DNA.In this review, we endeavor to discuss the types of bias introduced, the susceptibility of common WGA techniques to these bias types, and the interdependence between bias and characteristics of the template DNA. Finally, we attempt to illustrate some of the criteria specific to the analytical platform and research application that should be considered to enable combination of the appropriate WGA method, template DNA, sequencing platform, and intended use for optimal results.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users 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 76 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 76 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 21 28%
Student > Master 11 14%
Student > Bachelor 9 12%
Researcher 6 8%
Other 3 4%
Other 7 9%
Unknown 19 25%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 27 36%
Agricultural and Biological Sciences 13 17%
Computer Science 4 5%
Engineering 3 4%
Medicine and Dentistry 3 4%
Other 7 9%
Unknown 19 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 22 September 2018.
All research outputs
#6,425,431
of 22,828,180 outputs
Outputs from Methods in molecular biology
#1,946
of 13,125 outputs
Outputs of similar age
#88,025
of 353,128 outputs
Outputs of similar age from Methods in molecular biology
#147
of 997 outputs
Altmetric has tracked 22,828,180 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 13,125 research outputs from this source. They receive a mean Attention Score of 3.4. This one has done well, scoring higher than 84% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 353,128 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.
We're also able to compare this research output to 997 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.