Epistasis Methods and Protocols
This volume explores methods and protocols for detecting epistasis from genetic data. Chapters provide methods and protocols demonstrating approaches to identify epistasis, genetic epistasis testing, genome-wide epistatic SNP networks, epistasis detection through machine learning, and complex intera...
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| Format: | eBook |
| Language: | English |
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New York, NY
Humana
2021, 2021
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| Edition: | 1st ed. 2021 |
| Series: | Methods in Molecular Biology
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| Subjects: | |
| Online Access: | |
| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
Table of Contents:
- Mass-based Protein Phylogenetic Approach to Identify Epistasis
- SNPInt-GPU: Tool for epistasis testing with multiple methods and GPU acceleration
- Epistasis-based Feature Selection Algorithm
- W-test for Genetic Epistasis Testing
- The Combined Analysis of Pleiotropy and Epistasis (CAPE)
- Two-Stage Testing for Epistasis: Screening and Veri_cation
- Using Collaborative Mixed Models to Account for Imputation Uncertainty in Transcriptome-Wide Association Studies
- Phenotype Prediction under Epistasis
- Simulating Evolution in Asexual Populations with Epistasis
- Protocol for Construction of Genome-Wide Epistatic SNP Networks using WISH-R Package
- Brief survey on Machine Learning in Epistasis
- First-Order Correction of Statistical Significance for Screening Two-Way Epistatic Interactions
- Gene-Environment Interaction: AVariable Selection Perspective
- Using C-JAMP to Investigate Epistasis and Pleiotropy
- Identifying the Significant Change of Gene Expression in Genomic Series Data
- Analyzing High-Order Epistasis from Genotype-phenotype Maps Using ’Epistasis’ Package
- Deep Neural Networks for Epistatic Sequences Analysis
- Protocol for Epistasis Detection with Machine Learning Using GenEpi Package
- A Belief Degree Associated Fuzzy Multifactor Dimensionality Reduction Framework for Epistasis Detection
- Epistasis Detection Based on Epi-GTBN
- Epistasis Analysis: Classification through Machine Learning Methods
- Genetic Interaction Network Interpretation: A Tidy Data Science Perspective
- Trigenic Synthetic Genetic Array (τ-SGA) Technique for Complex Interaction Analysis