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Introduction

This package conducts fixed-effects (with inverse variance weighting) and random-effects (DerSimonian and Laird (1986)) meta-analyses of case-control or family-based (TDT) genetic data. In addition, catmap performs meta-analyses which combine these two types of study designs. Specifically, this package implements a fixed-effects model (Kazeem and Farrall (2005)) and a random-effects model (Nicodemus (2008)) for combined studies. This package was removed from the CRAN repository sometime after 2009. This is a rendition of the original package updated to work with the newest version of R. The algorithms have not changed since catmap version 1.6.0; however, this version has added some aesthetic improvements.

Quick start

The main function, catmap, accepts data.frame, matrix, or file input. See ?catmapdata for help.

library(catmap)
data(catmapdata)
catmapdata

##          name study  t nt caserisk controlrisk casenotrisk controlnotrisk
## 1  Peter,2002     2  0  0      316         338         220            218
## 2 Abrams,2001     2  0  0      710         146         422             96
## 3   Todd,2003     2  0  0     1004         344         233            543
## 4     Yu,2007     2  0  0     3344         434         544            322
## 5    Wei,2007     1 65 32        0           0           0              0

It is important to save the output of the catmap function for the next step in the analysis.

c1 <- catmap(catmapdata, 0.95, FALSE)

Four secondary functions use the output of the catmap function to build the meta-analysis figures, including the forest plot and the funnel plot. The functions below output these figures to the working directory as pdf files.

# Make forest plots
?catmap.forest
?catmap.sense
?catmap.cumulative

# Make funnel plot
?catmap.funnel

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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