README.md

In JohnHadish/DJ.GLM.GWAS: GLM GWAS

Homework 4

Statistical Genomics CROPS 545, Spring 2020 Professor: Zhiwu Zhang Due on March 30, 2020, Monday, 3:10PM, PST

Data files: You can used your own data or the following files that can be download at .

mdp_numeric.txt from GAPIT demo data. The data file contains 281 individuals (row wise) and 3093 SNPs (column wise) coded as 0/1/2.

mdp_SNP_information.txt. The file contains SNP ID, chromosome and position.

CROP545_Phenotype.txt. The file contains taxa name and phenotype.

CROP545_Covariates.txt. The file contains taxa name and two covariates.

Hand in: Each team (maximum of three people) email your report (PDF, limited to five page), R source code (text file), and user manual/tutorial (PDF, no page limitation) with email subject of “CROPS545 HW4” to . Name your files as following:

Homework4_PackageName.pdf and Homework4_PackageName.R

Grade components: 1) Hypothesis or statement; 2) Results; 3) Methods; 4 presentation; 5) R source code (clarity, simplicity and documenting comments)

Objectives: Develop your own R package to perform GLM GWAS.

The package should contain at least three input: y, X , and C that are R objects of numeric data frame. Their dimensions are n by 1, n by m, and n by t corresponding to phenotype, genotype and covariate data, where n is number of individuals, m is number of markers, and t is number of covariates. The function should return probability values with dimension of 1 by m for the association tests between phenotype and markers. Markers are tested one at a time with covariates in C included as covariates (15 points).

The package should perform PCA and incorporate PCs as cofactors for GWAS. Your package should also automatically exclude the PCs that are in linear dependent to the covariates provided by users. (25 points).

Develop a user manual and tutorials. Name your package and create a logo. (20 points).

Perform GWAS on the data provided or your own data which must contain cofactors (15 points).

Demonstrate that your method is superior to the competing method (GWASbyCor) through simulation with at least 30 replicates (25 points).

Extra credit

Demonstrate that your package is better than BLINK C version () on either statistical power or speed (25 points).

JohnHadish/DJ.GLM.GWAS documentation built on April 5, 2020, 9:05 p.m.