MixMAPexample: A working example of the MixMAP algorithm.
In gjm112/MixMAP: Implements the MixMAP Algorithm

Description Usage Format Details Source References Examples

Data containing the results of a meta-analysis consisting of many GWAS whose phenotype of interest is LDL cholesterol. This file contains all of the information necessary to run the MixMAP function directly without any pre-processing.

1	data(MixMAP_example)

A data frame with 31825 observations and the following five variables:

MarkerName: a character with SNP name

GC.Pvalue: a numeric with p-values for each SNP

Coordinate: integer containing the base pair location of the SNP within the chromosome

Chr: integer containing the chromsome number of the SNP

Gene: A character with gene symbol

This file contains all of the information needed to run the MixMAP function directly.

Nature 466, 707–713 (05 August 2010) The p-values in this file are from the paper Teslovich Et Al. (2009) “Biological, clinical and population relevance of 95 loci for blood lipids" Nature 466: 707–713. The phenotype of interest was low-density lipoprotein (LDL) cholesterol. The SNPs chosen are a subset that are found in the IBC array and have a unique gene name associated with them.

Foulkes, A.S., Matthews, G.J., Das, U., Ferguson, J., Reilly, M. (2013) “Mixed Modeling of Meta-Analysis P-Values (MixMAP) Suggests Multiple Novel Gene Loci for Low Density Lipoprotein Cholesterol". PLoS ONE 8(2): e54812.

Matthews, G.J. and Foulkes, A.S. (2015) “MixMAP: An R Package for Mixed Modeling of Meta-Analysis $p$ Values in Genetic Association Studies." Journal of Statistical Software. 66(3): 1-11.

library(MixMAP)	
#Load data
#This data has been prepared to be used as input to the MixMAP function directly
data(MixMAP_example)
str(MixMAP_example)

#Run mixmapTest
MixOut<-mixmapTest(MixMAP_example,pval="GC.Pvalue",snp="MarkerName",
  chr="Chr",coord="Coordinate",gene="Gene")
#Display first ten detected genes
summary(MixOut)
#MixManhattan Plot
plot(MixOut)