validate: Validate new datasets

In shbrief/PCAGenomicSignatures: Interpretation of RNA-seq experiments through robust, efficient comparison to public databases

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.

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")

shbrief/PCAGenomicSignatures documentation built on May 3, 2023, 11:21 a.m.