Build_AUCell_Rankings_Fast: Fast building AUCell gene rankings
In supatt-lab/SingCellaR: SingCellaR: an integrative analysis tool for single-cell RNA sequencing (scRNA-seq) data
View source: R/SingleCellRNASeq.R
Build_AUCell_Rankings_Fast R Documentation
Fast building AUCell gene rankings
Description
Fast building AUCell gene rankings
Usage
Build_AUCell_Rankings_Fast(
object,
AUCell_buildRankings.file = "",
nCores = NULL,
block.cell.size = 5000,
plotStats = FALSE
)
Arguments
object
The SingCellaR object.
AUCell_buildRankings.file
The output file of AUCell rankings.
nCores
The number of cores for running AUCell. Default 1
block.cell.size
The number of genes in each block of AUCell processing. Default 5000
plotStats
is logical. If TRUE, the AUCell stats will be displayed.
supatt-lab/SingCellaR documentation built on Aug. 24, 2023, 5:49 p.m.
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View source: R/SingleCellRNASeq.R
| Build_AUCell_Rankings_Fast | R Documentation |
Fast building AUCell gene rankings
Description
Fast building AUCell gene rankings
Usage
Build_AUCell_Rankings_Fast(
object,
AUCell_buildRankings.file = "",
nCores = NULL,
block.cell.size = 5000,
plotStats = FALSE
)
Arguments
object |
The SingCellaR object. |
AUCell_buildRankings.file |
The output file of AUCell rankings. |
nCores |
The number of cores for running AUCell. Default 1 |
block.cell.size |
The number of genes in each block of AUCell processing. Default 5000 |
plotStats |
is logical. If TRUE, the AUCell stats will be displayed. |
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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