R/print.cnv.R In CNVassoc: Association Analysis of CNV Data and Imputed SNPs

Documented in print.cnv

```print.cnv <-
function (x, digits = 4, ...)
{
cat("\n")
if (!is.null(attr(x, "mixture"))) {
cat("Inferred copy number variant by a quantitative signal\n")
if (is.null(attr(x, "batches")))
cat("   Method:", attr(x, "mixture")\$method, " \n\n")
else
cat("   Method:", attr(x, "mixture")[[1]]\$method, " \n\n")
}
else {
cat("-. Copy number variant\n   Input data: called probabilities\n")
}
cat("-. Number of individuals:", length(x), "\n")
cat("-. Copies", paste(attr(x, "num.copies"), collapse = ", "),
"\n")
if (!is.null(attr(x, "means"))){
means <- attr(x, "means")
if (is.vector(means))
cat("-. Estimated means:", paste(round(attr(x, "means"), digits = digits), collapse = ", "), "\n")
else{
colnames(means)<-paste("CNV",attr(x, "num.copies"))
cat("-. Estimated means:\n")
print(round(means, digits = digits))
}
}
if (!is.null(attr(x, "sds"))){
sds <- attr(x, "sds")
if (is.vector(sds))
cat("-. Estimated variances:", paste(round(attr(x, "sds")^2, digits = digits), collapse = ", "), "\n")
else{
colnames(sds)<-paste("CNV",attr(x, "num.copies"))
cat("-. Estimated variances:\n")
print(round(sds^2, digits = digits))
}
}
probs <- colMeans(attr(x, "probabilities"))
cat("-. Estimated proportions:", paste(round(probs, digits = digits), collapse = ", "), "\n")
if (!is.null(attr(x, "mixture"))){
if (is.null(attr(x, "batches"))){
if (!is.null(attr(x, "mixture")\$P))
cat("-. Goodness-of-fit test: p-value=", attr(x, "mixture")\$P,"\n")
}else{
if (!is.null(attr(x, "mixture")[[1]]\$P)){
cat("-. Goodness-of-fit test:\n")
p.values <- cbind(unlist(lapply(attr(x, "mixture"), function(mixture.i) mixture.i\$P)))
rownames(p.values)<-paste("Batch",unique(attr(x, "batches")))
colnames(p.values)<-"p-value"
print(p.values)
}
}
}
if (length(attr(x, "copynum.range")) > 1) {
if (!is.null(attr(x, "mixture")))
cat("\n\n-. Note: number of classes has been selected using the best BIC\n")
}
}
```

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CNVassoc documentation built on May 30, 2017, 12:50 a.m.