These function implement the MR method of Itzhak et al
robustMahalanobis(delta)
reprodScore(x, y, method = c("pearson"))
mrMethod(objectCond1, objectCond2, method = "2017")Arguments
- delta
The difference profile to compute the squared mahalanobis distance
- x
Numeric vector to compute reproducibility score
- y
Numeric vector to compute reproducibility score
- method
Correlation method. Default is Pearson
- objectCond1
A list of
MSnbase::MSnSets where each is an experimental replicate for the first condition, usually a control- objectCond2
A list of
MSnbase::MSnSets where each is an experimental replicate for the second condition, usually a treatment
Value
The squared Mahalanobis distance
The R score
The MR score of the Ithzak et al. 2016/2017
Examples
## Generate some example data
library("pRolocdata")
data("tan2009r1")
set.seed(1)
tansim <- sim_dynamic(object = tan2009r1,
numRep = 4L,
numDyn = 100L)
data <- tansim$lopitrep
control <- data[1:2]
treatment <- data[3:4]
## compute delta matrix
deltaMatrix <- exprs(control[[1]]) - exprs(treatment[[1]])
res <- bandle:::robustMahalanobis(deltaMatrix)
##' @examples
## Generate some example data
library("pRolocdata")
data("tan2009r1")
set.seed(1)
tansim <- sim_dynamic(object = tan2009r1,
numRep = 4L,
numDyn = 100L)
data <- tansim$lopitrep
control <- data[1:2]
treatment <- data[3:4]
## compute delta matrix
deltaMatrix1 <- exprs(control[[1]]) - exprs(treatment[[1]])
deltaMatrix2 <- exprs(control[[2]]) - exprs(treatment[[2]])
mr_score <- bandle:::reprodScore(deltaMatrix1, deltaMatrix2)
#> Warning: the standard deviation is zero
#> Warning: the standard deviation is zero
#> Warning: the standard deviation is zero
#> Warning: the standard deviation is zero
library(pRolocdata)
data("tan2009r1")
set.seed(1)
tansim <- sim_dynamic(object = tan2009r1,
numRep = 6L,
numDyn = 100L)
d1 <- tansim$lopitrep
control1 <- d1[1:3]
treatment1 <- d1[4:6]
mr1 <- mrMethod(objectCond1 = control1, objectCond2 = treatment1)
#> Warning: the standard deviation is zero
#> Warning: the standard deviation is zero
#> Warning: the standard deviation is zero
#> Warning: the standard deviation is zero
#> Warning: the standard deviation is zero
#> Warning: the standard deviation is zero
#> Warning: the standard deviation is zero
#> Warning: the standard deviation is zero
#> Warning: the standard deviation is zero
#> Warning: the standard deviation is zero
#> Warning: the standard deviation is zero
#> Warning: the standard deviation is zero
#> Warning: the standard deviation is zero
#> Warning: the standard deviation is zero
#> Warning: the standard deviation is zero
#> Warning: the standard deviation is zero
#> Warning: the standard deviation is zero
#> Warning: the standard deviation is zero
plot(mr1$Mscore, mr1$Rscore, pch = 21,
xlab = "MScore", ylab = "RScore")
