Different Statistical Models for KRN GWAS
Switch branches/tags
Nothing to show
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
GWAS3_proj
cache
data
doc
graphs
largedata
lib
profiling
table
.DS_Store
.gitignore
KRN_GWAS_v3.Rproj
README.md
setup_GWAS3.R

README.md

KRN-GWAS

This is a research repo for our project entitled "Empirical Comparisons of Different Statistical Modelsto Identify and Validate Kernel RowNumber-Associated Variants using NestedAssociation Mapping and Related Populations in Maize".

Introduction

In this study, we compared different statistical models for doing GWAS and cross-validated the KRN-associated variants identified in the initial GWAS using three unrelated populations. The KRN-associated variants identified in this study have the potential to enhance our understanding of the developmental steps involved in ear development.

Architecture about this Repo

This project contains ~400 commits. A largedata directory was intentionally ignored by adding to gitignore because of the large size of the files within the folder. To guide the visitors having a better idea about the repo, here we briefly introduce the functions or sepecific purposes of the directory system. The layout of directories is based on the idea from ProjectTemplate.

  1. cache: Here we store intermediate data sets that are generated during a preprocessing step.
  2. data: Here we store our raw data of small size. Data of large size, i.e. > 100M, store in a largedata folder that has been ignored using gitignore.
  3. doc: Documentation codes (i.e. Rmd files) for generating the figures.
  4. graphs: Graphs produced during the study.
  5. lib: Some functions for our work.
  6. profilling: Analysis scripts for the project. It contains some sub-directories.
  7. table: Table produced during the study.

Figures

Rmd code to generate some of the Figures in the paper.

License

This repo is free and open source for research usage, licensed under GPLv2.