PDMByKS: Compute phenotypic distance matrix by Kolmogorov-Smirnov...

In phenoDist: Phenotypic distance measures

Description

This function calculates the Kolmogorov-Smirnov statistic between a given sample and the negative control, for each feature, and then computes the phenotypic distance matrix based on the Kolmogorov-Smirnov statistics.

Usage

PDMByKS(x, unames, neg='rluc', selectedCellFtrs, distMethod=c('manhattan', 'euclidean', 'correlation', 'mahalanobis'))

Arguments

x	An imageHTS object.
unames	A character vector, containing the well names from where to collect the cell features. See getUnames for details.
neg	A character string to identify negative controls.
selectedCellFtrs	A character vector for cell features to be used in the calculation. If missing, all features are used.
distMethod	A character string indicating which distance method should be used. This must be (an abbreviation of) one of the strings 'manhattan', 'euclidean', 'correlation' or 'mahalanobis'.

Details

For each well, this function collects features of all cells, and performs a Kolmogorov-Smirnov test for each feature against the corresponding cell features from negative control wells, with the function ks.test of the stats package. The Kolmogorov-Smirnov statistics are collected for all wells and passed to PDMByWellAvg to calculate the phenotypic distance matrix.

Value

A symmetric distance matrix with the number of rows equaling to the length of unames.

Author(s)

Xian Zhang

See Also

ks.test, PDMByWellAvg

Examples

  library('phenoDist')

  ## load the imageHTS object
  load(system.file('kimorph', 'kimorph.rda', package='phenoDist'))
  x@localPath <- file.path(tempdir(), 'kimorph')

  ## calculate pair-wise svm distance matrix
  load(system.file('kimorph', 'selectedFtrs.rda', package='phenoDist'))
  pdm <- PDMByKS(x, unames=getUnames(x,plate=1, row=2:3, col=3), neg='rluc', selectedCellFtrs=selectedCellFtrs, distMethod='euclidean')
  pdm

phenoDist documentation built on May 2, 2018, 4:46 a.m.