- Name: Gota Morota
- Office: A218f Animal Science Building
- Email: morota@unl.edu
- Web: http://morotalab.org/
- Office Hours: By appointment

- Tues./Thurs. 9:30-10:45am
- Animal Science Building, Room A228

- ASCI 861U, 931, or equivalent
- STAT 802, 821, or equivalent
- Knowledge of statistical programming language R
- Searle, S.R. (1982)
*Matrix Algebra Useful for Statistics*. Wiley, New York. [Amazon]

- understand the statistical theory behind commonly used quantitative methods in genomics
- apply statistical methods to high-dimensional genomic data and analyze them using statistical computing tools
- critically review current literature in statistical and quantitative genetics

- [PDF]

- 1/10 (T): Course overview [HTML]
- 1/12 (R): Ordinary least-squares and the curse of dimensionality
- 1/17 (T): UNL classes canceled due to road conditions
- 1/19 (R): Variance, covariance, and linkage disequilibrium [HTML]
- 1/24 (T): Covariance between allelic counts [HW1]
- 1/26 (R): Review of average effect of allele substitution and breeding value
- 1/31 (T): Multi-locus additive genetic variance in the presence of linkage disequilibrium [HW2]
- 2/2 (R): Whole-genome regression - ridge regression 1 [R][P]
- 2/7 (T): Whole-genome regression - ridge regression 2
- 2/9 (R): HW1 review & Overview of likelihood-based inference
- 2/14 (T): Prediction of random effects - best prediction (BP) and best linear prediction (BLP)
- 2/16 (R): Prediction of random effects - best linear unbiased prediction (BLUP) and mixed model equations (MME) [HW3] [P]
- 2/21 (T): Prediction of random effects - mixed model equations (MME) [P]
- 2/23 (R): Relatedness due to genetic markers - additive genomic relationship
- 2/28 (T): Relatedness due to genetic markers - dominance genomic relationship 1
- 3/2 (R): Relatedness due to genetic markers - dominance genomic relationship 2 [HW4]
- 3/7 (T): HW2 review & Whole-genome regression - Genomic BLUP (GBLUP)
- 3/9 (R): Whole-genome regression - Ridge regression BLUP (RR-BLUP) & Cross-validation
- 3/14 (T): UNL Plant Breeding Symposium 2017 [WWW]
- 3/16 (R): HW3 review & Iterative methods for solving MME
- 3/21 (T): Spring break
- 3/23 (R): Spring break
- 3/28 (T): HW4 review and R packages to fit GBLUP/RR-BLUP [HW5][R]
- 3/30 (R): Iterative methods for solving MME & Genetic variance estimation with maximum likelihood (ML)
- 4/4 (T): Genetic variance estimation with restricted maximum likelihood (REML) & Whole-genome regression - Bayesian penalized regression models - Bayesian ridge regression [D]
- 4/6 (R): Whole-genome regression - Bayesian penalized regression models - Bayesian LASSO [HW6][R]
- 4/11 (T): Whole-genome regression - Bayesian penalized regression models - Bayesian alphabet - Bayes A, B, C, and Cpi & Population stratification - Mixed-linear-model association
- 4/13 (R): Population stratification - Mixed-linear-model association
- 4/18 (T): Whole-genome regression - Semi-parametric regression - Reproducing kernel Hilbert spaces regression [HW7][R]
- 4/20 (R): Guest lecture - Dr. Diego Jarquin
- 4/25 (T): Student presentations - 1
- 4/27 (R): Student presentations - 2 [HTML]
- 5/2 (T): Final exam - 10:00 a.m. to 12:00 p.m.