CONFESS (version 1.0.2)

Fluo_inspection: Fluo_inspection

Description

It generates the initial cell clusters as defined by their corrected fluorescence signals. The clusters can be generated by k-means (with GAP statistic estimated number of clusters) or by flow cytometry based approaches. This function shows the number and the characteristics of the initial groups and help us inspect cells' progression type for pathEstimator().

Usage

Fluo_inspection(data, altFUN = "kmeans", fixClusters = 0, SAM.sigma = 200, k.max = 15, B.kmeans = 50, savePlot = getwd(), seed = NULL)

Arguments

data

List. The output of getFluo() or getFluo_byRun().

altFUN

Character string. A user-defined method to generate the initial clusters. It can be one of kmeans, samSpec, fmeans,fmerge or fpeaks. Default is "kmeans".

fixClusters

Integer. A number that defines the number of k-mean clusters to be initially generated. If 0, the function runs GAP analysis to estimate the optimal number of clusters. Default is 0.

SAM.sigma

Integer. A value for the sigma parameter of SamSPECTRAL algorithm. Default is 200.

k.max

Integer. This is the maximum number of clusters that can be generated by k-means (if fixClusters = 0). Default is 15.

B.kmeans

Integer. The number of bootstrap samples for the calculation of the GAP statistic. Default is 50.

savePlot

Character string. Directory to store the plots. Its value can be an existing directory or "screen" that prints the plot only on the screen or "OFF" that does not generate a plot (suggested only during cross-validations). Default is the current working directory, getwd().

seed

Integer. An optional seed number for the Random Number Generator. Note that this seed is a 'reference' value of the actual seed used in sampling. CONFESS is using various random sampling methods. Each method's actual seed is factor*seed. The factors vary across methods. Default is NULL.

Value

A list of corrected fluorescence signal estimates and a helper plot for deciding the number of groups and the cell progression path. The output is essentially the output of getFluo() or getFluo_byRun() with the addition of the following components: GAPgroups: the groups estimated by one of the altFUN methods are depicted in the first column. The second column contains 1s for non-outlier signals and 2s for outlier signals (as estimated by each of the methods). clusterFUN: the altFUN method that has been used for clustering. normal.sigma: the sigma parameter of samSpec method. centroids: the 2 dimensional medians (centroids) of the estimated clusters. fixClusters: the fixClusters parameter used. Kmax: the k.meax parameter used. B.kmeans: the B.kmeans parameter used

Examples

step3 <- Fluo_inspection(data=step2.1,altFUN="kmeans",B.kmeans=5,savePlot="OFF")