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Bioinformatics

Overview of attention for book
Cover of 'Bioinformatics'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 3D Computational Modeling of Proteins Using Sparse Paramagnetic NMR Data.
  3. Altmetric Badge
    Chapter 2 Inferring Function from Homology.
  4. Altmetric Badge
    Chapter 3 Inferring Functional Relationships from Conservation of Gene Order.
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    Chapter 4 Structural and Functional Annotation of Long Noncoding RNAs.
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    Chapter 5 Construction of Functional Gene Networks Using Phylogenetic Profiles.
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    Chapter 6 Inferring Genome-Wide Interaction Networks.
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    Chapter 7 Integrating Heterogeneous Datasets for Cancer Module Identification.
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    Chapter 8 Metabolic Pathway Mining.
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    Chapter 9 Analysis of Genome-Wide Association Data.
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    Chapter 10 Adjusting for Familial Relatedness in the Analysis of GWAS Data.
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    Chapter 11 Analysis of Quantitative Trait Loci.
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    Chapter 12 High-Dimensional Profiling for Computational Diagnosis.
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    Chapter 13 Molecular Similarity Concepts for Informatics Applications.
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    Chapter 14 Compound Data Mining for Drug Discovery.
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    Chapter 15 Studying Antibody Repertoires with Next-Generation Sequencing.
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    Chapter 16 Using the QAPgrid Visualization Approach for Biomarker Identification of Cell-Specific Transcriptomic Signatures.
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    Chapter 17 Computer-Aided Breast Cancer Diagnosis with Optimal Feature Sets: Reduction Rules and Optimization Techniques.
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    Chapter 18 Inference Method for Developing Mathematical Models of Cell Signaling Pathways Using Proteomic Datasets.
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    Chapter 19 Clustering.
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    Chapter 20 Parameterized Algorithmics for Finding Exact Solutions of NP-Hard Biological Problems.
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    Chapter 21 Information Visualization for Biological Data.
Attention for Chapter 10: Adjusting for Familial Relatedness in the Analysis of GWAS Data.
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Chapter title
Adjusting for Familial Relatedness in the Analysis of GWAS Data.
Chapter number 10
Book title
Bioinformatics
Published in
Methods in molecular biology, January 2017
DOI 10.1007/978-1-4939-6613-4_10
Pubmed ID
Book ISBNs
978-1-4939-6611-0, 978-1-4939-6613-4
Authors

Russell Thomson, Rebekah McWhirter

Editors

Jonathan M. Keith

Abstract

Relatedness within a sample can be of ancient (population stratification) or recent (familial structure) origin, and can either be known (pedigree data) or unknown (cryptic relatedness). All of these forms of familial relatedness have the potential to confound the results of genome-wide association studies. This chapter reviews the major methods available to researchers to adjust for the biases introduced by relatedness and maximize power to detect associations. The advantages and disadvantages of different methods are presented with reference to elements of study design, population characteristics, and computational requirements.

Twitter Demographics

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

Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Other 1 20%
Student > Bachelor 1 20%
Student > Ph. D. Student 1 20%
Student > Master 1 20%
Researcher 1 20%
Other 0 0%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 2 40%
Agricultural and Biological Sciences 2 40%
Medicine and Dentistry 1 20%

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 05 June 2019.
All research outputs
#9,662,446
of 15,184,339 outputs
Outputs from Methods in molecular biology
#3,130
of 8,952 outputs
Outputs of similar age
#215,335
of 385,499 outputs
Outputs of similar age from Methods in molecular biology
#535
of 1,572 outputs
Altmetric has tracked 15,184,339 research outputs across all sources so far. This one is in the 23rd percentile – i.e., 23% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,952 research outputs from this source. They receive a mean Attention Score of 2.6. This one has gotten more attention than average, scoring higher than 55% 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 385,499 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,572 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 56% of its contemporaries.