validate {GenomicSuperSignature} | R Documentation

## Validate new datasets

### Description

Validate new datasets

### Usage

    validate(
      dataset,
      RAVmodel,
      method = "pearson",
      maxFrom = "PC",
      level = "max",
      scale = FALSE
    )

### Arguments

`dataset` | Single or a named list of SummarizedExperiment (RangedSummarizedExperiment, ExpressionSet or matrix) object(s). Gene names should be in 'symbol' format. Currently, each dataset should have at least 8 samples.
`RAVmodel` | PCAGenomicSignatures object.
`method` | A character string indicating which correlation coefficient is to be computed. One of "pearson" (default), "kendall", or "spearman": can be abbreviated.
`maxFrom` | Select whether to display the maximum value from dataset's PCs or avgLoadings. Under the default (`maxFrom="PC"`), the maximum correlation coefficient from top 8 PCs for each avgLoading will be selected as an output. If you choose (`maxFrom="avgLoading"`), the avgLoading with the maximum correlation coefficient with each PC will be in the output.
`level` | Output format of validated result. Two options are available: `c("max", "all")`. Default is "max", which outputs the matrix containing only the maximum coefficient. To get the coefficient of all 8 PCs, set this argument as "all". `level = "all"` can be used only for one dataset.
`scale` | Default is `FALSE`. If it is set to `TRUE`, dataset will be row normalized by rowNorm function.

### Value

A data frame containing the maximum pearson correlation coefficient between the top 8 PCs of the dataset and pre-calculated average loadings (in row) of training datasets (`score` column). It also contains other metadata associated with each RAV: `PC` for one of the top 8 PCs of the dataset that results in the given `score`, `sw` for the average silhouette width of the RAV, `cl_size` for the size of each RAV.

If the input for `dataset` argument is a list of different datasets, each row of the output represents a new dataset for test, and each column represents clusters from training datasets. If `level = "all"`, a list containing the matrices of the pearson correlation coefficient between all top 8 PCs of the datasets and avgLoading.

### Examples

    data(miniRAVmodel)
    library(bcellViper)
    data(bcellViper)
    validate(dset, miniRAVmodel)
    validate(dset, miniRAVmodel, maxFrom = "avgLoading")

[Package GenomicSuperSignature version 1.0.1 Index]