get.ari: Determine the adjusted rand index of a given feature

In uclahs-cds/public-R-NanoStringNormCNV: Helper Functions to Normalize NanoString CNV Data

Determine the adjusted rand index of a given feature

Description

Determine the adjusted rand index (ARI) of a given feature for continuous or discrete data

Usage

get.ari(data.to.cluster, feature, is.discrete = TRUE)

Arguments

data.to.cluster	A gene by sample data-frame to be clustered
feature	A vector with the variable of interest. Please note, it will be converted into a factor in the function. If the number of levels (unique elements) is less than 2, ARI will not be calculated.
is.discrete	Whether or not 'data.to.cluster' is discrete. If TRUE (default), Jaccard distance and ward clustering will be used and, if FALSE, Pearson correlation and complete clustering is used.

Details

Determine the adjusted rand index of a feature using clustered data (continuous or discrete).

Value

The adjusted rand index of feature

Author(s)

Cindy Yao and Emilie Lalonde

Examples

## Not run: 
	# load data
	data(NanoString.DNA.norm);
	data(PhenoData);

	# call CNAs
	cnas <- call.cnas.with.pooled.normals(
		normalized.data = NanoString.DNA.norm,
		phenodata = PhenoData
		);

	# evaluate results using replicates
	evaluation <- evaluate.replicates(
		phenodata = PhenoData,
		normalized.data = NanoString.DNA.norm,
		cna.rounded = cnas$rounded
		);
	
	## example 1
	# determine how well the copy number calls cluster by sample patient
	patient.ari <- get.ari(
		data.to.cluster = evaluation$cna.calls,
		feature = PhenoData[
			match(
				colnames(evaluation$cna.calls),
				PhenoData$SampleID
				),
			]$Patient,
		is.discrete = TRUE
		);

	## example 2
	# determine to what extent the normalized counts cluster by sample cartridge
	# log values, if appropriate
	if (all(unlist(NanoString.DNA.norm) >= 0)) {
	    count.data <- log10(NanoString.DNA.norm[, -c(1:3)] + 1);
	} else {
	    count.data <- NanoString.DNA.norm[, -c(1:3)];
	    }

	cartridge.ari <- get.ari(
	    data.to.cluster = count.data,
	    feature = PhenoData$Cartridge[
	    	match(
	    		colnames(NanoString.DNA.norm[, -(1:3)]),
	    		PhenoData$SampleID
	    		)
	    	],
	    is.discrete = FALSE
	    );

## End(Not run)

uclahs-cds/public-R-NanoStringNormCNV documentation built on May 31, 2024, 9:09 p.m.