EigenGWAS core
1
EigenGWAS basis
1.1
Genetic relatedness matrix
\(\mathbf{G}\)
1.1.1
Statistical properties of
\(\mathbf{G}\)
1.2
EigenGWAS linear model
1.2.1
\(\lambda_{GC}\)
correction
1.2.2
Threshold for EigenGWAS
1.3
Connection to singular value decomposition
1.4
Intepretation
1.4.1
\(F_{st}\)
1.4.2
Classic mechanic intepretation
2
Protocols
2.1
Protocols for selection
2.2
Protocal for EigenGWAS
2.3
Protocol for predicted eigenvectors
2.4
Nucleotide diversity
2.5
Other test statistics for selection
3
Resequencing studies
3.1
Technical review
3.1.1
Simulation
3.1.2
NGS
3.1.3
Chip data
3.1.4
GBS
3.2
Drop HWE test
4
Simulating population structure
4.1
Genetic drift
4.2
Discrete populations
4.3
Admixture populations
4.4
Homo & Heteogeneous
\(F_{st}\)
4.5
Wishart distribution
4.6
Tracy-Widom distribution
5
Data analysis
5.1
On-site examples
5.1.1
Arabdiopsis
5.1.2
3K rice
5.1.3
ALS
5.1.4
GF
5.1.5
UK birds
5.1.6
Darwin’s finches
5.1.7
GBS Maize
5.1.8
UK Biobank
5.2
Public datahub (NEO)
5.3
Meta-scale
5.3.1
\(n_e\)
5.3.2
\(m_e\)
6
Conclusion
6.1
Statistical power
6.2
Selection pattern
7
Appendix 1
7.1
Notes on linkage disequilibrium
7.2
The maximal value
\(\rho_{AB}\)
7.3
LD and recombination fraction
7.4
\(F_{st}\)
References
8
Notes
8.1
APY
8.1.1
A numerical example
8.2
LD score regression
8.3
Matrix inversion
wiki
8.3.1
2 X 2
8.3.2
3 X 3
9
IBD notes
9.1
HE association
9.2
IBD table
10
Appendix quick pca
10.1
Quck PCA method for snp matrix
Published with bookdown
EigenGWAS theory and application
References