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.
catmap(dataset, ci = 0.95, printout = FALSE)A data.frame, matrix, or file location.
The input should have the following column names: name, study, t, nt,
caserisk, controlrisk, casenotrisk, controlnotrisk. For a file location,
provide the data in a tab-delimited format. Note that the header must have
these exact columns and all cells in the table must have an entry, even
if the entry is 0 or NA. See catmapdata for an example.
A numeric value. The confidence level for confidence intervals; 0 < ci < 1.
A boolean. Toggles whether a text file of the models and Q statistic results should get saved to the working directory.
Use the output of the catmap function to generate figures using
secondary functions. These secondary functions produce output as either
a txt file, a pdf plot, or both.
A standard forest plot is available via catmap.forest.
A funnel plot is available via catmap.funnel. However,
no formal test of publication bias is available (see
[Ioannidis and Trikalinos (2007)]).
In addition, cumulative meta-analyses over time (catmap.cumulative)
and leave-one-out sensitivity analyses (catmap.sense) are
available for the fixed-effects estimates and random-effects estimates.
catmap, catmap.forest,
catmap.sense, catmap.cumulative,
catmap.funnel
data(catmapdata)
catmapobject <- catmap(catmapdata, 0.95, TRUE)
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