h.summary {ASSET} | R Documentation |
This function produces summary results from subset-based association analysis.
h.summary(rlist, level = 0.05, digits = 3)
rlist |
|
level |
Level for confidence intervals. Default is |
digits |
Number of significant digits to retain in odds ratios and confidence intervals in the summary table |
Returns a list of data frames containing p-values, odds-ratios, confidence intervals and the traits/types for each analysis.
The number of data frames in the list will depend on which function (h.traits
or h.types
)
was called and on the function options specified.
A list of data frames, one for each of the methods specified the original call of the functions h.traits
or h.types
. Each row of a data frame corresponds to a SNP and
the values include p-values for overall association (including component-wise p-values for two-sided search), names of phenotypes or disease subtypes included in
the best-subset, summary regression coefficients (e.g. log-odds-ratio for case-control studies) representing strength of association of a SNP with the
identified subset of traits/subtype and corresponding confidence intervals.
h.forestPlot
, h.traits
, h.types
# Use the example data data(ex_trait, package="ASSET") # Define the input arguments to h.traits snps <- as.vector(data[, "SNP"]) traits.lab <- paste("Trait_", 1:6, sep="") beta.hat <- as.matrix(data[, paste(traits.lab, ".Beta", sep="")]) sigma.hat <- as.matrix(data[, paste(traits.lab, ".SE", sep="")]) cor <- list(N11=N11, N00=N00, N10=N10) ncase <- diag(N11) ncntl <- diag(N00) # Now let us call h.traits on these summary data. res <- h.traits(snps, traits.lab, beta.hat, sigma.hat, ncase, ncntl, cor=cor, cor.numr=FALSE, search=NULL, side=2, meta=TRUE, zmax.args=NULL, meth.pval="DLM") h.summary(res)