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.

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
```

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