16xchen/Biomy: Novel tool to find genetic factors that drive a set of traits
Version 0.1

Biomy is a novel method of phenotype-to-gene linkage analysis (like QTL) that is much more efficient and accessible! It does not require an F2 cross or microarray data. The function {traittree} clusters a set of strains by their phenotypes, such as weight and blood pressure. Using a dataset of SNP data for those same strains, the function {maketree} scans through the entire SNP dataset to generate a large set of dendrograms, each clustering strains by consecutive 100 SNPs. csv files of SNP data for most strains can be found at opensource websites such as MGI, NCBI, or the University of North Carolina at Chapel Hill CSBio site. Correlating quantitative traits to Single Nucleotide Polymorphisms of strains. Next, the function {snpcor} runs correlation calculations with the trait dendrogram against each SNP dendrogram, and subsequently calculates Baker's correlation coefficients and the approximate location (bp) of the SNP. The function {snpcor.best} takes the correlation dataframe and subsets it into a smaller dataframe consisting of only SNPs with a correlation coefficient above a specified threshold. These are the most likely SNPs where causal genes are located. Finally, the function {drawtangle} visualizes the trait-SNP correlation by plotting out tanglegrams (two side by side dendrograms with lines connecting identical strains).

Getting started

Package details

AuthorXingyao Chen
MaintainerWho to complain to <[email protected]>
LicenseWhat license is it under?
Version0.1
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("devtools")
library(devtools)
install_github("16xchen/Biomy")
16xchen/Biomy documentation built on May 28, 2017, 6:58 p.m.