Description Usage Arguments Details Value Examples
Perform the single-marker meta-analysis with inflation adjustment. The inverse-variance weighting approach is used.
1 |
summary.files |
a character vector of file names containing the summary results of SNPs included in one or multiple studies. Each file must be able to be read by |
lambda |
a numeric vector of inflation factors. Each file in |
sel.snps |
a character vector of SNPs to be used in meta-analysis. The default is |
only.meta |
|
ambig.by.AF |
TRUE or FALSE to align SNPs with ambiguous alleles by allele frequency
(see |
The inverse-variance method is used by assuming a fixed effect model. The standard error is rescaled by sqrt{lambda}
.
meta
returns a list containing
meta.stat |
a data frame of summary statistics from meta-analysis. The summary statistics of individual studies specified in |
conf.snps |
a character vector of SNPs with conflictive allele information. |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | study1 <- system.file("extdata", package = "ARTP2", "study1.txt.gz")
study2 <- system.file("extdata", package = "ARTP2", "study2.txt.gz")
snps <- c('rs13266821', 'rs4824130', 'rs1792438', 'rs1000047',
'rs1000017', 'rs6066771', 'rs12508128')
m1 <- meta(summary.files = c(study1, study2), lambda = c(1.10, 1.08),
sel.snps = snps)
m2 <- meta(summary.files = c(study1, study2), lambda = c(1.10, 1.08),
sel.snps = snps, only.meta=FALSE)
m1$conf.snps
m1$meta.stat
m2$meta.stat
|
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