phewas-package: PheWAS analysis methods

In PheWAS/PheWAS: Phenome Wide Association Studies (PheWAS)

PheWAS analysis methods

Description

This package provides the tools necessary to perform a PheWAS analysis.

Details

Package:	PheWAS
Type:	Package
Version:	0.99.6-1
Date:	2023-05-31
License:	GPL3

This package contains the mappings and information for phecodes version 1.2 (ICD9CM) and the 2018 beta version of ICD10CM. With the package installed, the command vignette("PheWAS-package") will display the vignette. The examples on the PheWASExamples github repository provide some helpful guides, especially the V1.0 walkthrough here.

• mapCodesToPhecodes allows users to transform their ICD9CM and ICD10CM codes into phecodes.

• addPhecodeInfo allows users to add the description for phecodes.

• createPhenotypes takes code count data produces output suitable for PheWAS anaylsis.

• phewas allows users to perform a PheWAS analysis with genetics, ICD9 codes, phecodes, etc.

• phewasManhattan is a high level plot function that will generate a ggplot2 of PheWAS results.

• phenotypeManhattan provides a more general interface for plotting phenotype based Manhattan plots.

• phenotypePlot provides a complex interface for plotting many types of phenotype data.

• phewasMeta will perform a meta analysis of phewas results.

• generateExample creates data for example or testing purposes.

Author(s)

Robert Carroll <[e-mail]>

References

The original PheWAS manuscript can be found here: http://www.ncbi.nlm.nih.gov/pubmed/20335276

See Also

mapICD9ToPhecodes

addPhecodeInfo

createPhewasTable

phewas

PheWAS plotting methods

phewasMeta

Examples

#Load the PheWAS package
library(PheWAS)
#Set the random seed so it is replicable
set.seed(1)
#Generate some example data
ex=generateExample()
#Extract the three parts from the returned list
id.vocab.code.count=ex$id.vocab.code.count
genotypes=ex$genotypes
id.sex=ex$id.sex
#Create the phecode table- translates the codes, adds 
#exclusions, and reshapes to a wide format.
#Sum up the counts in the data where applicable.
phenotypes=createPhenotypes(id.vocab.code.count, 
  aggregate.fun=sum, id.sex=id.sex)
#Combine the data
data=inner_join(inner_join(phenotypes,genotypes),id.sex)
#Run the PheWAS
results=phewas_ext(data,phenotypes=names(phenotypes)[-1],genotypes=c("rsEXAMPLE"),
  covariates=c("sex"), cores=1)
#Plot the results
phewasManhattan(results, 
  title="My Example PheWAS Manhattan Plot")
#Add PheWAS descriptions
results_d=addPhecodeInfo(results)
#List the top 10 results
results_d[order(results_d$p)[1:10],]
#Create a nice interactive table (eg, in RStudio)
phewasDT(results)

PheWAS/PheWAS documentation built on July 3, 2023, 3:40 p.m.