analyse_sc_clusters | R Documentation |
Analyses cell clusters of a single-cell RNA-sequencing experiment to get pathway-level expressions for every cluster of cells.
analyse_sc_clusters(
object,
use_interactors = TRUE,
include_disease_pathways = FALSE,
create_reactome_visualization = FALSE,
create_reports = FALSE,
report_email = NULL,
verbose = FALSE,
...
)
object |
The object containing the single-cell RNA-sequencing data. |
use_interactors |
If set (default), protein-protein interactors from IntAct are used to extend Reactome pathways. |
include_disease_pathways |
If set, disease pathways are included as well. Disease pathways in Reactome follow a different annotation approach and can therefore lead to inaccurate results. |
create_reactome_visualization |
If set, the interactive visualization in Reactome's PathwayBrowser is created. |
create_reports |
If set, PDF and Microsoft Excel reports are created. Links to these report files are send to the supplied e-mail address. |
report_email |
The e-mail address to which reports should be sent to. |
verbose |
If set, additional status messages are printed. |
... |
Parameters passed to the specific implementation. Detailed documentations can be found there. |
There are currently two specific implementations of
this function, one to support Seurat
objects
and one to support Bioconductor's SingleCellExperiment
class.
A ReactomeAnalysisResult
object.
# This example shows how a Seurat object can be analysed
# the approach is identical for SingleCellExperiment objects
library(ReactomeGSA.data)
data(jerby_b_cells)
# perform the GSVA analysis
gsva_result <- analyse_sc_clusters(jerby_b_cells, verbose = FALSE)
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