Package 'flowDensity'

Title: Sequential Flow Cytometry Data Gating
Description: This package provides tools for automated sequential gating analogous to the manual gating strategy based on the density of the data.
Authors: Mehrnoush Malek,M. Jafar Taghiyar
Maintainer: Mehrnoush Malek <[email protected]>
License: Artistic-2.0
Version: 1.41.0
Built: 2024-12-22 06:05:18 UTC
Source: https://github.com/bioc/flowDensity

Help Index

Class "CellPopulation"

Description

This class represents the output of 'flowDensity(.)' function from flowDensity package.

Objects from the Class

Objects can be created by calls of the form new("CellPopulation", ...).

Slots

flow.frame:

Object of class "flowFrame" representing the flow cytometry data of the cell population

proportion:

Object of class "numeric" representing proportion of the cell population with respect to its parent cell population

cell.count:

Object of class "numeric" representing cell count of the cell population

channels:

Object of class "character" representing channel names corresponding to the 2 dimensions where the cell population is extracted

position:

Object of class "logical" representing position of the cell population in the 2-dimensional space

gates:

Object of class "numeric" representing thresholds on each channel used to gate the cell population

filter:

Object of class "matrix" representing boundary of the cell population using a convex polygon

index:

Object of class "numeric" representing indices of the data points in the cell population with respect to its parent cell population

Methods

flowDensity

signature(obj = "CellPopulation", channels = "ANY", position = "logical", singlet.gate = "missing"): ...

flowDensity

signature(obj = "CellPopulation", channels = "missing", position = "missing", singlet.gate = "logical"): ...

getflowFrame

signature(obj = "CellPopulation"): ...

plot

signature(x = "flowFrame", y = "CellPopulation"): ...

Author(s)

Jafar Taghiyar <email: <[email protected]>>

Examples

showClass("CellPopulation")

1D density gating method

Description

Find the best threshold for a single channel in flow cytometry data based on its density distribution.

Usage

deGate(obj,channel, n.sd = 1.5, use.percentile = FALSE,  percentile =NA,use.upper=FALSE, upper = NA,verbose=TRUE,twin.factor=.98,
                   bimodal=F,after.peak=NA,alpha = 0.1, sd.threshold = FALSE, all.cuts = FALSE,
                   tinypeak.removal=1/25, adjust.dens = 1,count.lim=20,magnitude=.3,slope.w=4,seq.w = 4, spar = 0.4, ...)

Arguments

obj

obj: a 'FlowFrame' object, 'CellPopulation' or 'GatingHierarchy'

channel

a channel's name or its corresponding index in the 'flow.frame'.

n.sd

an integer coefficient for the standard deviation to determine the threshold based on the standard deviation if 'sd.threshold' is TRUE.

use.percentile

if TRUE, forces to return the 'percentile'th threshold.

percentile

A value in [0,1] that is used as the percentile. The default is NA. If set to a value(n) and use.percentile=F, it returns the n-th percentile, for 1-peak populations.

use.upper

Logical. If TRUE, forces to return the inflection point based on the first (last) peak if upper=F (upper=T). Default value is set to 'FALSE'

upper

if TRUE, finds the change in the slope at the tail of the density curve, if FALSE, finds it at the head. Default value is set to 'NA'.

verbose

Logical. If TRUE, Prints a message if only one peak is found, or when inflection point is used to set the gates.

twin.factor

a value in [0,1] that is used to exclude twinpeaks

bimodal

Logical. If TRUE, it returns a cutoff that splits population closer to 50-50, when there are more than two peaks.

after.peak

Logical. If TRUE, it returns a cutoff that is after the maximum peaks, when there are more than two peaks.

alpha

a value in [0,1) specifying the significance of change in the slope being detected. This is by default 0.1, and typically need not be changed.

sd.threshold

if TRUE, uses 'n.sd' times standard deviation as the threshold. Default value is set to 'FALSE'.

all.cuts

if TRUE, returns all the identified cutoff points, i.e. potential thresholds for that channel. Default value is set to 'FALSE'.

tinypeak.removal

A number in [0,1] to exclude/include tiny peaks in density distribution.

adjust.dens

The smoothness of density in [0,Inf] to be used in density(.). The default value is 1 and should not be changed unless necessary

count.lim

minimum limit for events count in order to calculate the threshold. Default is 20, returning NA as threshold.

magnitude

A value between 0 and 1, for tracking a slope and reporting changes that are smaller than magnitude*peak_height

slope.w

window.width for tracking slope. Default is 4, calculating a slope based on 4 points before and after the current point.

seq.w

value used for making the sequence of density points, used in trackSlope.

spar

value used in smooth.spline function, used in generating the density, default is 0.4.

...

Extra arguments to be passed to smoothSpline function.

Details

deGate works for GatingHierarchy, flowFrame, CellPopulation object or a numeric vector of data. In case the input is a numeric vector, channel doesn't need to provided, but the rest of arguments can be used to tune the outcome.

Value

an integer value (vector) of cutoff(s), i.e. threshold(s), on the specified channel

Author(s)

Mehrnoush Malek <[email protected]>

See Also

getflowFrame notSubFrame flowDensity

Examples

data_dir <- system.file("extdata", package = "flowDensity")
load(list.files(pattern = 'sampleFCS_1', data_dir, full = TRUE))
#Find the threshold for CD20
cd19.gate <- deGate(f,channel="PerCP-Cy5-5-A")
# Gate out the CD20- populations using the notSubFrame
plotDens(f,c("APC-H7-A","PerCP-Cy5-5-A"))
abline(h=cd19.gate,lty=3,col=2)

Methods for Function flowDensity in Package flowDensity

Description

Methods for function flowDensity in package flowDensity

Arguments

obj

GatingHierarchy or CellPopulationobject

channels

a vector of two channel names or their corresponding indices.

position

a vector of two logical values specifying the position of the cell subset of interest on the 2D plot.

...

This can be used to pass one of the following arguments:

  • 'use.percentile' if TRUE, returns the 'percentile'th threshold.

  • 'percentile' a value in [0,1] that is used as the percentile if 'use.percentile' is TRUE.

  • 'upper' if 'TRUE', it finds the change in the slope after the peak with index 'peak.ind'.

  • 'use.upper' if 'TRUE', forces to return the inflection point based on the first (last) peak if upper=F (upper=T)

  • 'twin.factor' a value in [0,1] that is used to exclude twinpeaks.

  • 'bimodal' If TRUE, it returns a cutoff that splits population closer to 50-50, when there are more than two peaks.

  • 'after.peak' If TRUE, it returns a cutoff that is after the maximum peaks, when there are more than two peaks.

  • 'sd.threshold' if TRUE, it uses 'n.sd' times standard deviation for gating.

  • 'n.sd' an integer that is multiplied to the standard deviation to determine the place of threshold if 'sd.threshold' is 'TRUE'.

  • 'tinypeak.removal' a vector of length 2, for sensitivity of peak finding for each channel. See deGate() for more information.

  • 'filter' If provided it uses the given filter to gate the population.

  • 'use.control' if TRUE, it finds the threshold using a matched control population and uses it for gating.

  • 'control' a 'flowFrame' or 'CellPopulation' object used for calculating the gating threshold when 'use.control' is set to TRUE. If a control population is used, the other arguments ('upper', 'percentile', etc.) are applied to the control data when finding the threshold (i.e. not to 'obj').

  • 'alpha' a value in [0,1) specifying the significance of change in the slope which would be detected. This is by default 0.1, and typically need not be changed.

  • 'ellip.gate' if TRUE, it fits an ellipse on the data as a gate, otherwise the rectangle gating results are returned

  • 'scale' a value in [0,1) that scales the size of ellipse to fit if 'ellip.gate' is TRUE

Value

a CellPopulation object.

'CellPopulation' class accessor.

Description

an accessor for 'CellPopulation' class to get its 'FlowFrame' object. This will remove all the NA values in the frame.

Usage

getflowFrame(obj)

Arguments

obj

a 'CellPopulation' object.

Value

a 'FlowFrame' object.

Author(s)

Jafar Taghiyar <[email protected]>

Examples

data_dir <- system.file("extdata", package = "flowDensity")
load(list.files(pattern = 'sampleFCS_1', data_dir, full = TRUE))
lymph <- flowDensity(obj=f, channels=c('FSC-A', 'SSC-A'),
                     position=c(TRUE, NA))
f.lymph <- getflowFrame(lymph)

Finding Peaks

Description

Find all peaks in density along with their indices

Usage

getPeaks(obj, channel,tinypeak.removal=1/25, adjust.dens=1,verbose=F,twin.factor=1,spar = 0.4,...)

Arguments

obj

a 'FlowFrame', 'GatingHierarchy', 'CellPopulation' a density object or a numeric vector of density.

channel

a channel's name or its corresponding index. If the input is numeric vector, channel is NA.

tinypeak.removal

A number in [0,1] to exclude/include tiny peaks in density distribution. Default is 1/25.

adjust.dens

The smoothness of density in [0,Inf] to be used in density(.). The default value is 1 and should not be changed unless necessary

verbose

If TRUE, printing warnings.

twin.factor

If smaller than 1, peaks that are of greater than hieght as the maximum peak*twin.factor will be removed.

spar

argument to pass to smoothSpline function, default value of spar is 0.4.

...

Other arguments that can be passed to smoothSpline function.

Value

a list, including peaks, their corresponding indices and height.

Author(s)

Mehrnoush Malek <[email protected]>

See Also

deGate notSubFrame flowDensity

Examples

data_dir <- system.file("extdata", package = "flowDensity")
load(list.files(pattern = 'sampleFCS_1', data_dir, full = TRUE))
#Find the threshold for CD20
peaks <- getPeaks(f,channel="PerCP-Cy5-5-A",tinypeak.removal=1/30)
peaks

Preprocessing helper function for flow cytometry data

Description

Remove the margin events on the axes. Usually, these events are considered as debris or artifacts. This is specifically useful for 'FSC' and 'SSC' channels in a 'FlowFrame' object. However, any channel can be input as an argument.

Usage

nmRemove(  flow.frame, channels, neg=FALSE, verbose=FALSE,return.ind=FALSE)

Arguments

flow.frame

a 'FlowFrame' object.

channels

a vector of channel names or their corresponding indices.

neg

if TRUE, negative events are also removed

verbose

if TRUE, it prints the margin event in each channel

return.ind

if TRUE, it return indices of margin events for each channel.

Value

a 'FlowFrame' object, or a 'list' of indices identifying margin events for each channel.

Author(s)

Jafar Taghiyar <[email protected]> Mehrnoush Malek <[email protected]>

Examples

data_dir <- system.file("extdata", package = "flowDensity")
load(list.files(pattern = 'sampleFCS_2', data_dir, full = TRUE))
#Removing margin events of FSC-A and SSC-A channels
no.margin <- nmRemove(f2, c("FSC-A","SSC-A"),verbose=TRUE)
plotDens(f2, c("FSC-A","SSC-A"))
# Scatter plot of FSC-A vs. SSC-A after removing margins
plotDens(no.margin, c("FSC-A","SSC-A"))

Removing a subset of a FlowFrame object

Description

Remove a subset of a FlowFrame object specified by gates from the flowDensity method. It comes in handy when one needs the complement of a cell population in the input flow cytometry data.

Usage

notSubFrame(obj, channels, position = NA, gates, filter)

Arguments

obj

a 'FlowFrame' or 'cellPopulation' object.

channels

a vector of two channel names or their corresponding indices in the 'flow.frame'.

position

a vector of two logical values specifying the position of the cell subset of interest on the 2D plot.

gates

the gates slot in the CellPoulation object which is output by flowDensity function. It can also be a vector of two integer values each of which specifies a threshold for the corresponding channel in 'channels' argument.

filter

boundary of the subset to be removed. This value is stored in the 'filter' slot of a 'CellPopulation' object.

Value

a CellPopulation object.

Author(s)

Mehrnoush Malek <[email protected]>

Examples

data_dir <- system.file("extdata", package = "flowDensity")
load(list.files(pattern = 'sampleFCS_1', data_dir, full = TRUE))
#Find the threshold for CD20
cd20.gate <- deGate(f,channel="APC-H7-A")
# Gate out the CD20- populations using the notSubFrame
CD20.pos <- notSubFrame(f,channels=c("APC-H7-A","PerCP-Cy5-5-A"),position=c(FALSE,NA),gates=c(cd20.gate,NA))
#Plot the CD20+ cells on same channels
plotDens(CD20.pos@flow.frame,c("APC-H7-A","PerCP-Cy5-5-A"))

Plot flow cytometry data with density-based colors

Description

Generate a scatter dot plot with colors based on the distribution of the density of the provided channels.

Usage

plotDens(obj, channels ,col, main, xlab, ylab, xlim,ylim, pch=".", density.overlay=c(FALSE,FALSE),count.lim=20, dens.col=c("grey48","grey48"),cex=1,
dens.type=c("l","l"),transparency=1, adjust.dens=1,show.contour=F, contour.col="darkgrey", verbose=TRUE,...)

Arguments

obj

a 'FlowFrame', or 'cellPopulation' object.

channels

a vector of two channel names or their corresponding indices in the 'flow.frame'.

col

A specification for the default plotting color: see '?par'.

main

an overall title for the plot: see '?plot'

xlab

a title for the x axis: see '?plot'

ylab

a title for the y axis: see '?plot'

xlim

a range for the x axis: see '?plot'

ylim

a range for the y axis: see '?plot'

pch

Either an integer specifying a symbol or a single character to be used as the default in plotting points: see '?par'.

density.overlay

Logical vector of length 2, to plot density overlays on the x and y axes. Default is c(FALSE,FALSE).

count.lim

Cutoff for number of events to set color. Default is 20. Samples with less than 20 cells will be plotted in black.

dens.col

2-character string giving the color of plot desired for density curves.

cex

Size of the points for the plot. For more information look at ?plot in graphics.

dens.type

2-character string giving the type of plot desired.

transparency

Transparency of the bi-variate plot, to see the densitu curves in the background. The lower it is, the more transparent the plot is.

adjust.dens

The smoothness of density in [0,Inf] to be used in density(.). The default value is 1 and should not be changed unless necessary

show.contour

Default is FALSE. It add the contourLines to plot.

contour.col

Color for contourLines. Default is darkgrey.

verbose

Default is True. It will add that the sample has 0 cells in the plot title.

...

can be used to provide desired arguments for the plot() function used to plot the output results.

Value

a scatter dot plot with density-based colors, along with density overlays if desired. Set xlim and ylim when plotting if you would like to have all your plots to have same range on the axes (specially when density.overlay=TRUE)

Author(s)

Mehrnoush Malek <[email protected]> Jafar Taghiyar <[email protected]>

Examples

data_dir <- system.file("extdata", package = "flowDensity")
load(list.files(pattern = 'sampleFCS_1', data_dir, full = TRUE))
#Plot CD3 vs. CD19 to see the distribution of cell populations and their density
plotDens(f,c("V450-A","PerCP-Cy5-5-A"))