A common task in expression analysis is to collapse multiple features that are mapped to the same gene by some statistic. This function does this job by keeping the matrix row (normally features) with the higheest statistic specified by the user.
A numeric matrix
A vector of character giving the keys the rows are mapped to. A common scenario is that each row represents one probeset, while the vector keys give the genes that the probesets are mapped to. Thus keys can be redundant, namely multiple probesets can map to the same gene.
Logical, whether rows with NA as their keys should
be kept (TRUE) or should be discarded (FALSE)
The function to calculate the univariate statistic. By default
the NA-robust mean is used.
How should the information of the levels of keys, e.g. unique
keys, be kept. dicard will discard this information, rownames
will make the unique keys (potentially with NAs) as row names of the
output matrix, and attribute will append an attribute named
levels to the output matrix.
Other parameters passed to the stat function
A numeric matrix with rows mapped to unique keys, selected by the maximum statistics. See examples below
isMaxStatRow returns a logical vector, with rows with maximal
statistics each key as TRUE and otherwise as FALSE.
keepMaxStatRowInd returns the integer indices of such rows. Finally
keepMaxStatRow returns the resulting matrices.
For use see examples
myFun1 <- function(x) mean(x, na.rm=TRUE)
myFun2 <- function(x) sd(x, na.rm=TRUE)
mat1 <- matrix(c(1,3,4,-5,
0,1,2,3,
7,9,5,3,
0,1,4,3), ncol=4, byrow=TRUE)
keys1 <- c("A", "B", "A", "B")
isMaxStatRow(mat1, keys1, stat=myFun1)
#> [1] FALSE FALSE TRUE TRUE
isMaxStatRow(mat1, keys1, stat=myFun2)
#> [1] TRUE FALSE FALSE TRUE
keepMaxStatRowInd(mat1, keys1, stat=myFun1)
#> [1] 3 4
keepMaxStatRowInd(mat1, keys1, stat=myFun2)
#> [1] 1 4
keepMaxStatRow(mat1, keys1, stat=myFun1)
#> [,1] [,2] [,3] [,4]
#> A 7 9 5 3
#> B 0 1 4 3
keepMaxStatRow(mat1, keys1, stat="myFun2")
#> Error in get(stat, envir = parent.frame()): object 'myFun2' not found
keepMaxStatRow(mat1, keys1, stat="myFun2", levels="discard")
#> Error in get(stat, envir = parent.frame()): object 'myFun2' not found
keepMaxStatRow(mat1, keys1, stat="myFun2", levels="attribute")
#> Error in get(stat, envir = parent.frame()): object 'myFun2' not found
mat2 <- matrix(c(1,3,4,5,
0,1,2,3,
7,9,5,3,
0,1,4,3,
4,0,-1,3.1,
9,4,-3,2,
8,9,1,2,
0.1,0.2,0.5,NA,
NA, 4, 3,NA), ncol=4, byrow=TRUE,
dimnames=list(LETTERS[1:9], NULL))
keys2 <- c("A", "B", "A", "B", NA, NA, "C", "A", "D")
isMaxStatRow(mat2, keys2, keepNArows=FALSE, stat=myFun1)
#> [1] FALSE FALSE TRUE TRUE FALSE FALSE TRUE FALSE TRUE
keepMaxStatRowInd(mat2, keys2, keepNArows=FALSE, stat=myFun1)
#> [1] 3 4 7 9
keepMaxStatRow(mat2, keys2, keepNArows=FALSE, stat=myFun1)
#> [,1] [,2] [,3] [,4]
#> A 7 9 5 3
#> B 0 1 4 3
#> C 8 9 1 2
#> D NA 4 3 NA
keepMaxStatRow(mat2, keys2, keepNArows=TRUE, stat=myFun1)
#> [,1] [,2] [,3] [,4]
#> A 7 9 5 3.0
#> B 0 1 4 3.0
#> <NA> 4 0 -1 3.1
#> <NA> 9 4 -3 2.0
#> C 8 9 1 2.0
#> D NA 4 3 NA
keepMaxStatRow(mat2, keys2, keepNArows=TRUE, stat=myFun1, levels="discard")
#> [,1] [,2] [,3] [,4]
#> C 7 9 5 3.0
#> D 0 1 4 3.0
#> E 4 0 -1 3.1
#> F 9 4 -3 2.0
#> G 8 9 1 2.0
#> I NA 4 3 NA
keepMaxStatRow(mat2, keys2, keepNArows=TRUE, stat=myFun1, levels="attribute")
#> [,1] [,2] [,3] [,4]
#> C 7 9 5 3.0
#> D 0 1 4 3.0
#> E 4 0 -1 3.1
#> F 9 4 -3 2.0
#> G 8 9 1 2.0
#> I NA 4 3 NA
#> attr(,"levels")
#> [1] "A" "B" NA NA "C" "D"