QTL mapping of muscle weight traits in C57BL/6J x DBA/2J AIL mouse study
This repository contains code and data to accompany publication of
Peter Carbonetto, Riyan Cheng, Joseph Gyekis, Clarissa Parker, David Blizard, Abraham Palmer and Arimantas Lionikas (2014). Discovery and refinement of muscle weight QTLs in B6 x D2 advanced intercross mice. Physiological Genomics 46: 571-582.
Copyright (c) 2014, Peter Carbonetto
The b6d2muscle project repository is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
This program is distributed in the hope that it will be useful, but without any warranty; without even the implied warranty of merchantability or fitness for a particular purpose. See LICENSE for more details.
Overview of data files
Here is a brief summary of the files in the data directory:
pheno.csv Muscle weight measurements and other phenotypes for 891 mice derived from the B6 and D2 inbred strains.
geno.F8.csv Genotype data for 425 F8 mice derived from the B6 and D2 inbred strains.
map.F8.csv Information about SNPs genotyped in F8 mice.
geno.csv Genotype data for 435 F9-F13 mice derived from the B6 and D2 inbred strains.
map.csv Information about SNPs genotyped in F9-F13 mice.
Overview of R source code files
Here is a brief summary of the files in the code directory:
map.qtls.combined.R This is the main script for mapping muscle weight QTLs in the B6 x D2 advanced intercross line. This script separately analyzes data from the F8 cross, data from the F9-F13 crosses, and data from the combined F8-F13 sample, comparing two different methods for mapping QTLs: (1) a simple linear regression approach that does not correct for possible confounding due to relatedness ('qtl'); and (2) a linear mixed model that uses marker-based estimates of pairwise relatedness to correct for possible confounding due to unequal relatedness ('QTLRel'). This script also includes an option for modeling sex-specific genetic effects on muscle weights.
plot.gwscan.combined.R Plots the QTL mapping results generated by the map.qtls.combined.R script.
examine.pheno.R A small script to view the distribution of the muscle weight phenotypes in the F8 and F9-F13 cohorts.
mapping.functions.R Functions for QTL mapping and analyzing the experimental cross data.
map.cross.rr.R Function used to map QTLs separately on each chromosome using QTLRel.
The R code implementing the analysis procedures was developed by:
Dept. of Human Genetics
University of Chicago