Version: | 1.2-2 |
Date: | 2023-05-29 |
Title: | Filtering of Flow Cytometry Samples |
Imports: | feature, geometry, hdrcde, ks, misc3d, ptinpoly, rgl, KernSmooth |
Description: | Filtering, also known as gating, of flow cytometry samples using the curvHDR method, which is described in Naumann, U., Luta, G. and Wand, M.P. (2010) <doi:10.1186/1471-2105-11-44>. |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
NeedsCompilation: | yes |
Maintainer: | Matt Wand <matt.wand@uts.edu.au> |
Packaged: | 2023-05-29 04:35:14 UTC; mwand |
Author: | Matt Wand [aut, cre], George Luta [aut], Ulrike Naumann [aut], Mathew W. McLean [ctb], Dai Feng [ctb], Luke Tierney [ctb], Florian Hahne [ctb] |
Repository: | CRAN |
Date/Publication: | 2023-05-29 15:50:06 UTC |
Internal curvHDR functions.
Description
Internal curvHDR functions.
Details
These are not to be called by the user.
Filtering via the curvHDR method.
Description
Filter univariate or bivariate data using the curvHDR method. The motivating application is flow cytometry, where the filters endeavour to mimic human-perceived gates.
Usage
curvHDRfilter(x, HDRlevel, growthFac = NULL, signifLevel = 0.05,
bwFac = 1, gridsize = NULL, removeDebri = TRUE,
minSampSize = NULL, HpiGridSize = NULL, quiet = TRUE,
graphChk = FALSE)
Arguments
x |
array containing the input data, typically corresponding
to flow cytometric
measurements. |
HDRlevel |
number between 0 and 1 corresponding to the level of the highest density region within each high curvature region. |
growthFac |
growth factor parameter. High curvature regions are grown
to have ‘volume’ |
signifLevel |
number between 0 and 1 corresponding to the
significance level for curve region determination. The default value
of |
bwFac |
bandwidth factor. The default bandwidth is multiplied
by |
gridsize |
vector of number of grid points in each direction |
removeDebri |
Boolean flag for removal of ‘debri’ points in the
input data. The default value of |
minSampSize |
curvHDR regions with less than |
HpiGridSize |
gridsize used for plug-in bandwidth
selection in the case where the input data
is trivariate. The default value of
|
quiet |
Boolean flag for ‘quiet’
running. If |
graphChk |
Boolean flag for graphical checking. If |
Value
data |
the input data (for use in plotting). |
insideFilter |
logical variable indicating the rows of the input data matrix corresponding to points inside the curvHDR filter. |
polys |
the curvHDR filter. Depending on the dimension d this is a list of intervals (d=1), polygons (d=2) or polyhedra (d=3). |
HDRlevel |
highest density region level |
Author(s)
G. Luta, U. Naumann and M.P. Wand
References
Naumann, U., Luta, G. and Wand, M.P. (2009).
The curvHDR method for gating flow cytometry samples.
BMC Bioinformatics, 11:44, 1-13.
See Also
Examples
library(curvHDR)
# Univariate curvHDR examples:
xUniv <- c(rnorm(1000,-2),rnorm(1000,2))
gate1a <- curvHDRfilter(xUniv)
plot(gate1a)
print(gate1a$poly) # List of intervals that define gate1a.
## Not run: print(gate1a$insideFilter) # Indicators of inclusion of
# xUniv inside gate1a.
## End(Not run)
gate1b <- curvHDRfilter(xUniv,HDRlevel=0.5)
plot(gate1b)
print(gate1b$poly) # List of intervals that define gate1b.
## Not run: print(gate1b$insideFilter) # Indicators of inclusion of
# xUniv inside gate1b.
## End(Not run)
# Bivariate curvHDR examples:
xBiva <- cbind(c(rnorm(1000,-2),rnorm(1000,2)),
c(rnorm(1000,-2),rnorm(1000,2)))
## Not run: gate2a <- curvHDRfilter(xBiva)
plot(gate2a)
print(gate2a$poly) # List of polygon vertices that define gate2a.
print(gate2a$insideFilter) # Indicators of inclusion of
# xBiva inside gate2a.
## End(Not run)
## Not run:
gate2b <- curvHDRfilter(xBiva,HDRlevel=0.5)
plot(gate2b)
print(gate2b$poly) # List of polygon vertices that define gate2b.
print(gate2b$insideFilter) # Indicators of inclusion of
# xBiva inside gate2b.
## End(Not run)
# Trivariate curvHDR examples:
## Not run:
xTriv <- cbind(c(rnorm(1000,-2),rnorm(1000,2)),
c(rnorm(1000,-2),rnorm(1000,2)),
c(rnorm(1000,-2),rnorm(1000,2)))
gate3a <- curvHDRfilter(xTriv)
plot(gate3a)
print(gate3a$poly) # List of polyhedron elements that define gate3a.
print(gate3a$insideFilter) # Indicators of inclusion of
# xTriv inside gate3a.
## End(Not run)
## Not run:
gate3b <- curvHDRfilter(xTriv,HDRlevel=0.5)
plot(gate3b)
print(gate3b$poly) # List of polyhedron elements that define gate3b.
print(gate3b$insideFilter) # Indicators of inclusion of
# xTriv inside gate3b.
## End(Not run)
Display the package's vignette.
Description
The vignette of the curvHDR package is displayed using the default PDF file browser. It provides a detailed detailed description of use of the package for gating flow cytometry data using the curvHDR method.
Usage
curvHDRvignette()
Author(s)
Matt Wandmatt.wand@uts.edu.au, G. Lutagl77@georgetown.edu and U. Naumannulrike.naumann1@gmail.com
Examples
if(interactive())
{
curvHDRvignette()
}
Plot a curvHDR filter.
Description
Takes an object of class curvHDR
,
produced by curvHDRfilter()
, and then plots
it together with (a subset of) the data.
Usage
## S3 method for class 'curvHDRfilter'
plot(x,removeDebri=TRUE,pch=NULL,cex=NULL,
bty=NULL,col=NULL,main=NULL,...)
Arguments
x |
a fitted |
removeDebri |
Boolean flag for removal of ‘debri’ points in the
input data. The default value of |
pch |
Plotting character specification. |
cex |
Character expansion factor. |
bty |
Box-type for the plotting frame. |
col |
Colour of the points. |
main |
Main label on the plot. |
... |
Other graphical parameters. |
Value
The function generates a plot.
Author(s)
G. Luta, U. Naumann and M.P. Wand
References
Naumann, U., Luta, G. and Wand, M.P. (2009).
The curvHDR method for gating flow cytometry samples.
BMC Bioinformatics, 11:44, 1-13.
See Also
Examples
library(curvHDR)
# Univariate curvHDR example:
xUniv <- c(rnorm(1000,-2),rnorm(1000,2))
gate1 <- curvHDRfilter(xUniv)
plot(gate1)
# Bivariate curvHDR example:
xBiva <- cbind(c(rnorm(1000,-2),rnorm(1000,2)),
c(rnorm(1000,-2),rnorm(1000,2)))
gate2 <- curvHDRfilter(xBiva)
plot(gate2)
# Trivariate curvHDR example:
## Not run:
xTriv <- cbind(c(rnorm(1000,-2),rnorm(1000,2)),
c(rnorm(1000,-2),rnorm(1000,2)),
c(rnorm(1000,-2),rnorm(1000,2)))
gate3 <- curvHDRfilter(xTriv)
plot(gate3)
## End(Not run)