lotrrs {gateR} | R Documentation |
A single gate for two conditions
Description
Estimates a ratio of relative risk surfaces and computes the asymptotic p-value surface for a single gate with two conditions. Includes features for basic visualization. This function is used internally within the gating
function to extract the points within the significant areas. This function can also be used as a standalone function.
Usage
lotrrs(
dat,
bandw = NULL,
alpha = 0.05,
p_correct = "none",
nbc = NULL,
plot_gate = FALSE,
save_gate = FALSE,
name_gate = NULL,
path_gate = NULL,
rcols = c("#FF0000", "#CCCCCC", "#0000FF"),
lower_lrr = NULL,
upper_lrr = NULL,
c1n = NULL,
c2n = NULL,
win = NULL,
...,
doplot = lifecycle::deprecated(),
verbose = lifecycle::deprecated()
)
Arguments
dat |
Input data frame flow cytometry data with five (5) features (columns): 1) ID, 2) Condition A ID, 3) Condition B ID, 4) Marker A as x-coordinate, 5) Marker B as y-coordinate. |
bandw |
Optional, numeric. Fixed bandwidth for the kernel density estimation. Default is based on the internal |
alpha |
Numeric. The two-tailed alpha level for significance threshold (default is 0.05). |
p_correct |
Optional. Character string specifying whether to apply a correction for multiple comparisons including a False Discovery Rate |
nbc |
Optional. An integer for the number of bins when |
plot_gate |
Logical. If |
save_gate |
Logical. If |
name_gate |
Optional, character. The filename of the visualization. The default is "gate". |
path_gate |
Optional, character. The path of the visualization. The default is the current working directory. |
rcols |
Character string of length three (3) specifying the colors for: 1) group A (numerator), 2) neither, and 3) group B (denominator) designations. The defaults are |
lower_lrr |
Optional, numeric. Lower cut-off value for the log relative risk value in the color key (typically a negative value). The default is no limit, and the color key will include the minimum value of the log relative risk surface. |
upper_lrr |
Optional, numeric. Upper cut-off value for the log relative risk value in the color key (typically a positive value). The default is no limit, and the color key will include the maximum value of the log relative risk surface. |
c1n |
Optional, character. The name of the level for the numerator of condition A. The default is NULL, and the first level is treated as the numerator. |
c2n |
Optional, character. The name of the level for the numerator of condition B. The default is NULL, and the first level is treated as the numerator. |
win |
Optional. Object of class |
... |
Arguments passed to |
doplot |
|
verbose |
|
Details
This function estimates a ratio of relative risk surfaces and computes the asymptotic p-value surface for a single gate with two conditions using three successive risk
functions. A relative risk surface is estimated for Condition A at each level of Condition B, and then a ratio of the two relative risk surfaces is computed.
RR_{Condition B1} = \frac{Condition A2 of B1}{Condition A1 of B1}
RR_{Condition B2} = \frac{Condition A2 of B2}{Condition A1 of B2}
ln(rRR) = ln\left (\frac{RR_{Condition B2}}{CRR_{Condition B2}}\right )
The p-value surface of the ratio of relative risk surfaces is estimated assuming asymptotic normality of the ratio value at each gridded knot. The bandwidth is fixed across all layers. Basic visualization is available if plot_gate = TRUE
.
Provides functionality for a correction for multiple testing. If p_correct = "FDR"
, calculates a False Discovery Rate by Benjamini and Hochberg. If p_correct = "uncorrelated Sidak"
, calculates an independent Sidak correction. If p_correct = "uncorrelated Bonferroni"
, calculates an independent Bonferroni correction. If p_correct = "correlated Sidak"
or if p_correct = "correlated Bonferroni"
, then the corrections take into account the into account the spatial correlation of the surface. (NOTE: If p_correct = "correlated Sidak"
or if p_correct = "correlated Bonferroni"
, it may take a considerable amount of computation resources and time to calculate). If p_correct = "Adler and Hasofer"
or if p_correct = "Friston"
, then calculates a correction based on Random Field Theory. If p_correct = "none"
(the default), then the function does not account for multiple testing and uses the uncorrected alpha
level. See the internal pval_correct
function documentation for more details.
The two condition variables (Condition A and Condition B) within dat
must be of class 'factor' with two levels. The first level in each variable is considered the numerator (i.e., "case") value, and the second level is considered the denominator (i.e., "control") value. The levels can also be specified using the c1n
and c2n
parameters.
Value
An object of class 'list' where each element is a object of class 'rrs' created by the risk
function with two additional components:
rr
An object of class 'im' with the relative risk surface.
f
An object of class 'im' with the spatial density of the numerator.
g
An object of class 'im' with the spatial density of the denominator.
P
An object of class 'im' with the asymptotic p-value surface.
lrr
An object of class 'im' with the log relative risk surface.
alpha
A numeric value for the alpha level used within the gate.
Examples
test_lotrrs <- lotrrs(dat = randCyto)