celldebris_emclustering: identifies Synechococcus cyanobacteria cells and Debris in a...

In cyanoFilter: Cyanobacteria Population Identification for Flow Cytometry

Description

separates BS4, BS5 and Debris population in a flowfile using an EM style algorithm. Algorithm starts with ncluster number of clusters and automatically reduces this number if need be.

Usage

celldebris_emclustering(flowfile, channels, mu = NULL, sigma = NULL,
  ncluster = 5, min.itera = 20, classifier = 0.8)

Arguments

flowfile	flowframe to be clustered.
channels	channels to use for the clustering
mu	pre-specified mean matrix for the clusters. Number of rows should equal ncluster and number of columns should equal length(channels). Defaults to NULL and will be computed from the data internally if left as NULL.
sigma	pre-specified list of variance-covariace matrix for the clusters. Each element of the list should contain a square matrix of variance-covariance matrix with length equal ncluster. Defaults to NULL and will be computed from the data internally if left as NULL.
ncluster	number of cluster desired.
min.itera	minimum number of EM iterations.
classifier	cells will be assigned to a cluster if belongs to that cluster by at least this probability. Only for plotting purposes.

Details

The function using EM algorithm involving mixtures of multivariate normals to separate the entire cell-population provided into cluster. The mvnorm function is used to compute the densities and only the probabilites of each point belonging to a cluster are returned as additional columns to the expression matrix of result.

Value

list containing;

• percentages - percentage of cells in each cluster

• mus - matrix of mean vectors for each cluster

• sigmas - list of variance-covariance matrix for each cluster

• result - flowframe with probabilities of each cluster added as columns to the expression matrix of the flowfile

See Also

celldebris_nc

Examples

flowfile_path <- system.file("extdata", "B4_18_1.fcs", package = "cyanoFilter",
              mustWork = TRUE)
flowfile <- flowCore::read.FCS(flowfile_path, alter.names = TRUE,
                               transformation = FALSE, emptyValue = FALSE,
                               dataset = 1) #FCS file contains only one data object
flowfile_nona <- cyanoFilter::nona(x = flowfile)
flowfile_noneg <- cyanoFilter::noneg(x = flowfile_nona)
flowfile_logtrans <- lnTrans(x = flowfile_noneg, c('SSC.W', 'TIME'))
cells_nonmargin <- cellmargin(flow.frame = flowfile_logtrans, Channel = 'SSC.W',
           type = 'estimate', y_toplot = "FSC.HLin")

emapproach <- celldebris_emclustering(flowfile = cells_nonmargin$reducedflowframe,
                    channels = c("RED.B.HLin", "YEL.B.HLin",
                    "FSC.HLin", "RED.R.HLin"),
                    ncluster = 5, min.itera = 20)

cyanoFilter documentation built on Jan. 9, 2020, 5:08 p.m.