tSNE {CATALYST} | R Documentation |
Runs t-SNE dimensionality reduction on a daFrame
.
tSNE(x, ...) ## S4 method for signature 'daFrame' tSNE(x, cols_to_use = NULL, n = 1000, verbose = TRUE, seed = 42)
x |
a |
... |
optional arguments. |
cols_to_use |
a character vector. Specifies which antigens to use for clustering.
If NULL, the function will attempt to use the |
n |
numeric. Specifies the number of cells to downsample to per sample. |
verbose |
logical. Should information on progress be reported? |
seed |
numeric. Specifies the seed to be set before sampling |
Writes the tSNE coordinates and the indicies of the events used
for their computation into the metadata slot of the input daFrame
.
Helena Lucia Crowell crowellh@student.ethz.ch
Nowicka M, Krieg C, Weber LM et al. CyTOF workflow: Differential discovery in high-throughput high-dimensional cytometry datasets. F1000Research 2017, 6:748 (doi: 10.12688/f1000research.11622.1)
# construct daFrame data(PBMC_fs, PBMC_panel, PBMC_md) re <- daFrame(PBMC_fs, PBMC_panel, PBMC_md) # run t-SNE lineage <- c("CD3", "CD45", "CD4", "CD20", "CD33", "CD123", "CD14", "IgM", "HLA_DR", "CD7") re <- tSNE(re, cols_to_use=lineage, n=50) par(pty="s") tsne <- S4Vectors::metadata(re)$tsne$Y plot(tsne, pch=20)