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Genome-Wide Association Studies

Overview of attention for book
Genome-Wide Association Studies
Springer US

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Designing a Genome-Wide Association Study: Main Steps and Critical Decisions
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    Chapter 2 Preparation and Curation of Phenotypic Datasets
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    Chapter 3 Genotyping Platforms for Genome-Wide Association Studies: Options and Practical Considerations
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    Chapter 4 Genome-Wide Association Study Statistical Models: A Review
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    Chapter 5 Interpretation of Manhattan Plots and Other Outputs of Genome-Wide Association Studies
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    Chapter 6 Preparation and Curation of Multiyear, Multilocation, Multitrait Datasets
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    Chapter 7 Development, Preparation, and Curation of High-Throughput Phenotypic Data for Genome-Wide Association Studies: A Sample Pipeline in R
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    Chapter 8 Preparation and Curation of Omics Data for Genome-Wide Association Studies
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    Chapter 9 Producing High-Quality Single Nucleotide Polymorphism Data for Genome-Wide Association Studies
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    Chapter 10 A Practical Guide to Using Structural Variants for Genome-Wide Association Studies
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    Chapter 11 Data Integration, Imputation Imputation , and Meta-analysis Meta-analysis for Genome-Wide Association Studies
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    Chapter 12 Population Structure and Relatedness for Genome-Wide Association Studies
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    Chapter 13 Performing Genome-Wide Association Studies with Multiple Models Using GAPIT
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    Chapter 14 Performing Genome-Wide Association Studies Using rMVP
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    Chapter 15 Identification and Validation of Candidate Genes from Genome-Wide Association Studies
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    Chapter 16 Biparental Crossing and QTL Mapping for Validation of Genome-Wide Association Studies
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    Chapter 17 Development of Breeder-Friendly KASP Markers from Genome-Wide Association Studies Results
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    Chapter 18 Mapping Major Disease Genes in Soybean by Genome-Wide Association Studies
  20. Altmetric Badge
    Chapter 19 GWAS Case Studies in Wheat
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    Chapter 20 Plant Microbiome-Based Genome-Wide Association Studies
Attention for Chapter 13: Performing Genome-Wide Association Studies with Multiple Models Using GAPIT
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About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (62nd percentile)

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Citations

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Chapter title
Performing Genome-Wide Association Studies with Multiple Models Using GAPIT
Chapter number 13
Book title
Genome-Wide Association Studies
Published in
Methods in molecular biology, June 2022
DOI 10.1007/978-1-0716-2237-7_13
Pubmed ID
Book ISBNs
978-1-07-162236-0, 978-1-07-162237-7
Authors

Wang, Jiabo, Tang, You, Zhang, Zhiwu

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 13 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 23%
Student > Ph. D. Student 2 15%
Unspecified 1 8%
Professor 1 8%
Unknown 6 46%
Readers by discipline Count As %
Agricultural and Biological Sciences 4 31%
Biochemistry, Genetics and Molecular Biology 2 15%
Unspecified 1 8%
Engineering 1 8%
Unknown 5 38%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 03 June 2022.
All research outputs
#15,756,637
of 23,485,953 outputs
Outputs from Methods in molecular biology
#5,329
of 13,354 outputs
Outputs of similar age
#246,603
of 443,949 outputs
Outputs of similar age from Methods in molecular biology
#167
of 441 outputs
Altmetric has tracked 23,485,953 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,354 research outputs from this source. They receive a mean Attention Score of 3.4. This one has gotten more attention than average, scoring higher than 56% 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 443,949 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 441 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 62% of its contemporaries.