1. GWAS/QTL Apps Overview
CyVerse Workshop
GWAS/QTL Apps Overview

2. Advantages
Population type, phenotype data, environments, size of dataset…
All the compute power you need—with a million snps you may need more, with many phenotypes you may need more
Options to suit your needs
Atmosphere for testing, analyses that run on few resources, and visualization
Discovery Environment for apps that are likely to be used often and don’t require too many resources
Agave API installs for very large data analyses, will be able to expose as DE app

3. Consideration:
Population type, phenotype data, environments, size of dataset
Historical population requires fitting of population structure
Use FaST-LMM, Structure then TASSEL, GEMMA
Environments?
Fit covariates as fixed with FaST-LMM, GEMMA,
fit as random with QXPak, R packages such as lme4, aml adaptive lasso
small-n structured populations can also benefit from subgroup adjustment, as may not be equal/HW
Discuss fixed vs random definition
Define prediction as having some data with genotype but no measured trait, want to predict trait value
Predictions—use GenSel app, BATools
Already in Atmosphere
Already in Discovery Environment

4. Many methods out there
Some applications will be easier than others to use and install
If installed already—just figure out which parameters you want to set
Aaron will talk about this more tomorrow (use known-truth simulations to see what works)
Check that the parameters you need are visible
Installing an app
Will it in run in your Atmosphere allocation? Install and do a test run!
If not, install via Agave API
--ask for help as needed, iPlant can provide software engineering and install support via Extended Collaborative Support form and short review process

5. What do you need to do your own g2p data analysis?
Input data (BTW, GBS tools are available to get snps, BISQUE to help get phenotype values from images)
File-format conversion—you may need to write a script if your dataset is very large
Suitable analysis application for genotype-phenotype association—can be a pain to match your needs to what is out there, get statistical help
Visualization of output—may need to use graphics package in Atmosphere or a commercial one that you like on your own computer

6. Some applications will be easier than others to use and install…
Open source best
Computationally efficient (C, fortran) if possible
Large user community, developers available

7. Success stories:
API used to associate g2p: very large number of metabolites measured in a very large number of genotypes
iPlant staff assisted
GenSel installed by developers, made available through the DE
For whole-genome predictions, widely used in breeding

8. Detailed instructions with videos, manuals, documentation in
Keep asking: ask.iplantcollabortive.org