fitNorm2: Fit bivariate normal distribution.

In prada: Data analysis for cell-based functional assays

Description

Fits a bivariate normal distribution into a data set of paired values and selects data points according to their standard deviation from the fitted distribution.

Usage

fitNorm2(x, y=NA, scalefac=1, method="covMcd", noise, gateName = "fitNorm")

Arguments

x	Numeric vector containing x-value or n by 2 matrix containing x and y values or object of class cytoFrame.
y	Numeric vector containing y-value (optional). The length of x must be the same as that of y.
scalefac	Numeric vector giving factor of standard deviations used for data selection (all points within scalefac standard deviations are selected).
method	One of covMcd or cov.rob defining method used for computation of covariance matrix.
noise	Numeric or logical index vector defining value pairs in x that are not used for fitting of distributions. Can be used to deal with noisy data.
gateName	Character giving the name of the gate object.

Details

Computes the densities of a bivariate normal distribution from the covariance matrix of the paired data. Covariance matrices are acquired either by function covMcd (considerably faster) or by function cov.rob.

Value

A list containing items mu (midpoint of distribution), S (covariance matrix), p (density values for each data pair), sel (selection of data points), scalefac (factor of standard deviations used for data selection), data (x and y values of data points) and gate, an object of class gate containing the selection.

Author(s)

Florian Hahne

See Also

cov.rob, covMcd, plotNorm2

Examples

 sampdat <- readFCS(system.file("extdata",
   "fas-Bcl2-plate323-04-04.A01", package="prada"))
 nfit    <- fitNorm2(exprs(sampdat[,1:2]), scalefac=2)
 plotNorm2(nfit, selection=TRUE, ellipse=TRUE) 

Example output

Loading required package: Biobase
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, sd, var, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, basename, cbind, colMeans, colSums, colnames,
    dirname, do.call, duplicated, eval, evalq, get, grep, grepl,
    intersect, is.unsorted, lapply, lengths, mapply, match, mget,
    order, paste, pmax, pmax.int, pmin, pmin.int, rank, rbind,
    rowMeans, rowSums, rownames, sapply, setdiff, sort, table, tapply,
    union, unique, unsplit, which, which.max, which.min

Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.

Loading required package: RColorBrewer
Loading required package: grid
Loading required package: rrcov
Loading required package: robustbase

Attaching package: 'robustbase'

The following object is masked from 'package:Biobase':

    rowMedians

Scalable Robust Estimators with High Breakdown Point (version 1.4-7)

prada documentation built on April 28, 2020, 7:52 p.m.