.loadingCor {GenomicSuperSignature} | R Documentation

## Validating new dataset

### Description

Validating new dataset

### Usage

    .loadingCor(dataset, avgLoading, method = "pearson", scale = FALSE)

### Arguments

`dataset` | A gene expression profile to be validated. Different classes of objects can be used including ExpressionSet, SummarizedExperiment, RangedSummarizedExperiment, or matrix. Rownames (genes) should be in symbol format. If it is a matrix, genes should be in rows and samples in columns.
`avgLoading` | A matrix with genes by RAVs.
`method` | A character string indicating which correlation coefficient is to be computed. One of "pearson" (default), "kendall", or "spearman": can be abbreviated.
`scale` | Default is `FALSE`. If it is set to `TRUE`, dataset will be row normalized by rowNorm function.

### Value

A matrix of Pearson correlation coefficient (default, defined through `method` argument) between RAVs (row) and the top 8 PCs from the datasets (column)

[Package GenomicSuperSignature version 1.0.1 Index]