run.phenograph: run.phenograph - Run phenograph clustering
In sydneycytometry/Spectre: A computational toolkit in R for the integration, exploration, and analysis of high-dimensional single-cell cytometry data.
Description
Usage
Arguments
Value
Author(s)
References
Examples
View source: R/run.phenograph.R
Description
This function allows you to perform phenograph clustering on a data.table
Usage
1
Arguments
ref.dat
NO DEFAULT. A data.table consisting of the 'refernece' data you will use to train the alignment algorithm
Value
Returns a data.table with clustering results added
Author(s)
Thomas M Ashhurst, thomas.ashhurst@sydney.edu.au
References
Ashhurst, T. M., et al. (2019). https://www.ncbi.nlm.nih.gov/pubmed/31077106
Examples
1
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cell.dat <- Spectre::demo.asinh
cell.dat <- Spectre::do.subsample(cell.dat, 5000)
use.cols <- names(cell.dat)[c(11:19)]
cell.dat <- run.phenograph(dat = cell.dat, use.cols = use.cols)
sydneycytometry/Spectre documentation built on March 20, 2021, 2:15 a.m.
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Description Usage Arguments Value Author(s) References Examples
View source: R/run.phenograph.R
Description
This function allows you to perform phenograph clustering on a data.table
Usage
1 |
Arguments
ref.dat |
NO DEFAULT. A data.table consisting of the 'refernece' data you will use to train the alignment algorithm |
Value
Returns a data.table with clustering results added
Author(s)
Thomas M Ashhurst, thomas.ashhurst@sydney.edu.au
References
Ashhurst, T. M., et al. (2019). https://www.ncbi.nlm.nih.gov/pubmed/31077106
Examples
1 2 3 4 5 6 | cell.dat <- Spectre::demo.asinh
cell.dat <- Spectre::do.subsample(cell.dat, 5000)
use.cols <- names(cell.dat)[c(11:19)]
cell.dat <- run.phenograph(dat = cell.dat, use.cols = use.cols)
|
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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