subtract_baseline {autonomics} | R Documentation |
Subtract baseline level within block
subtract_baseline( object, subgroupvar, subgroupctr = slevels(object, subgroupvar)[1], block = NULL, assaynames = setdiff(assayNames(object), "weights"), verbose = TRUE ) subtract_pairs( object, subgroupvar, subgroupctr = slevels(object, subgroupvar)[1], block, assaynames = setdiff(assayNames(object), "weights"), verbose = TRUE ) subtract_differences(object, block, subgroupvar, verbose = TRUE)
object |
SummarizedExperiment |
subgroupvar |
subgroup svar |
subgroupctr |
control subgroup |
block |
block svar (within which subtraction is performed) |
assaynames |
which assays to subtract for |
verbose |
TRUE/FALSE |
subtract_baseline
subtracts baseline levels within block, using the
medoid baseline sample if multiple exist.
subtract_pairs
also subtracts baseline level within block.
It cannot handle multiple baseline samples, but has instead been optimized
for many blocks
subtract_differences
subtracts differences between subsequent levels,
again within block
SummarizedExperiment
# read require(magrittr) file <- download_data('atkin18.metabolon.xlsx') object0 <- read_metabolon(file, plot=FALSE) pca(object0, plot=TRUE, color=SET) # subtract_baseline: takes medoid of baseline samples if multiple object <- subtract_baseline(object0, block='SUB', subgroupvar='SET') pca(object, plot=TRUE, color=SET) # subtract_pairs: optimized for many blocks object <- subtract_pairs( object0, block='SUB', subgroupvar='SET') pca(object, plot=TRUE, color=SET) # subtract differences object <- subtract_differences(object0, block='SUB', subgroupvar='SET') values(object) %<>% na_to_zero() pca(object, plot=TRUE, color=SET)