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eQTL Analysis

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Cover of 'eQTL Analysis'

Table of Contents

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    Book Overview
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    Chapter 1 Introductory Methods for eQTL Analyses
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    Chapter 2 Performing QTL and eQTL Analyses with the R-Package GenomicTools
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    Chapter 3 eQTL Mapping Using Transcription Factor Affinity
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    Chapter 4 Identification and Quantification of Splicing Quantitative Trait Loci
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    Chapter 5 Genome-Wide Composite Interval Mapping (GCIM) of Expressional Quantitative Trait Loci in Backcross Population
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    Chapter 6 Combining eQTL and SNP Annotation Data to Identify Functional Noncoding SNPs in GWAS Trait-Associated Regions
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    Chapter 7 Statistical and Machine Learning Methods for eQTL Analysis
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    Chapter 8 Sparse Regression Models for Unraveling Group and Individual Associations in eQTL Mapping
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    Chapter 9 Exploring Bayesian Approaches to eQTL Mapping Through Probabilistic Programming
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    Chapter 10 High-Order Association Mapping for Expression Quantitative Trait Loci
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    Chapter 11 Integration of Multi-omics Data for Expression Quantitative Trait Loci (eQTL) Analysis and eQTL Epistasis
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    Chapter 12 Sparse Partial Least Squares Methods for Joint Modular Pattern Discovery
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    Chapter 13 Expression Quantitative Trait Loci (eQTL) Analysis in Cancer
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    Chapter 14 QTL Analysis Beyond eQTLs
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    Chapter 15 Quantitative Trait Loci (QTL) Mapping
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    Chapter 16 Expression Quantitative Trait Loci Analysis in Multiple Tissues
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    Chapter 17 Tissue-Specific eQTL in Zebrafish
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Title
eQTL Analysis
Published by
Springer US, January 2020
DOI 10.1007/978-1-0716-0026-9
ISBNs
978-1-07-160025-2, 978-1-07-160026-9
Editors

Xinghua Mindy Shi

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X Demographics

The data shown below were collected from the profiles of 6 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 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 7 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 43%
Researcher 1 14%
Unknown 3 43%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 2 29%
Agricultural and Biological Sciences 1 14%
Unknown 4 57%