Perform over-representation analysis (ORA) on a scDiffCom object, with the possibility to define new categories in addition to the standard ones supported by default.
RunORA(
object,
categories = c("LRI", "LIGAND_COMPLEX", "RECEPTOR_COMPLEX", "ER_CELLTYPES",
"EMITTER_CELLTYPE", "RECEIVER_CELLTYPE", "GO_TERMS", "KEGG_PWS"),
extra_annotations = NULL,
overwrite = TRUE,
verbose = TRUE
)# S4 method for scDiffCom
RunORA(
object,
categories = c("LRI", "LIGAND_COMPLEX", "RECEPTOR_COMPLEX", "ER_CELLTYPES",
"EMITTER_CELLTYPE", "RECEIVER_CELLTYPE", "GO_TERMS", "KEGG_PWS"),
extra_annotations = NULL,
overwrite = TRUE,
verbose = TRUE
)
A scDiffCom object with updated slot ora_table
.
scDiffCom
object
Names of the standard categories on which to perform ORA.
Default is all standard categories, namely
c("LRI", "LIGAND_COMPLEX", "RECEPTOR_COMPLEX", "ER_CELLTYPES",
"EMITTER_CELLTYPE", "RECEIVER_CELLTYPE", "GO_TERMS", "KEGG_PWS")
Convenience parameter to perform ORA on user-defined
non-standard categories. If NULL
(default), ORA is
performed only on standard categories from categories
. Otherwise it
must be a list of data.tables
or data.frames (see Details).
If TRUE
(default), previous results are overwritten
in case they correspond to a category passed in categories
.
If TRUE
(default), progress messages are printed.
Additional user-defined ORA categories can be added via the
parameter extra_annotations
. The data.frames or data.tables in this
list must have exactly two columns that indicates a relationship between
values from a standard category (first column) to values of the new
category (second column). As a typical example, this
vignette
shows how to perform ORA on cell type families attached to each cell type.