kmeansNormalize: Perform k-means clustering, normalize anscombe data and...

In CSSQ: Chip-seq Signal Quantifier Pipeline

Description

This function performs normalization on the anscombe transformed data by clustering them using k-means algorithmn and utilizing the information from clusters. It returns an DataFrame object normalized counts, cluster information and the variance of that cluster for that sample.

Usage

kmeansNormalize(ansDataVec, numClusters = 4)

Arguments

ansDataVec	Anscombe transformed count data for a sample.
numClusters	A number indicating the number of clusters to use for k-means clustering. (default: 4)

Value

DataFrame containing the normalized counts, cluster information and the variance of the cluster in the sample.

See Also

normalizeData which iterates over this function.

Examples

exCount <- c(1,2,3,4,5,6,7,8,9,10)
kmeansEx <- kmeansNormalize(exCount,numClusters=2)
kmeansEx

CSSQ documentation built on Nov. 8, 2020, 6:47 p.m.