Perform t-SNE dimensionality reduction
Runs t-SNE on the normalized cell factors (or raw cell factors) to generate a 2D embedding for visualization. Has option to run on subset of factors. Note that running multiple times will reset tsne.coords values.
runTSNE( object, use.raw = FALSE, dims.use = 1:ncol(object@H.norm), use.pca = FALSE, perplexity = 30, theta = 0.5, method = "Rtsne", fitsne.path = NULL, rand.seed = 42 )
object |
|
use.raw |
Whether to use un-aligned cell factor loadings (H matrices) (default FALSE). |
dims.use |
Factors to use for computing tSNE embedding (default 1:ncol(H.norm)). |
use.pca |
Whether to perform initial PCA step for Rtsne (default FALSE). |
perplexity |
Parameter to pass to Rtsne (expected number of neighbors) (default 30). |
theta |
Speed/accuracy trade-off (increase for less accuracy), set to 0.0 for exact TSNE (default 0.5). |
method |
Supports two methods for estimating tSNE values: Rtsne (Barnes-Hut implementation of t-SNE) and fftRtsne (FFT-accelerated Interpolation-based t-SNE) (using Kluger Lab implementation). (default Rtsne) |
fitsne.path |
Path to the cloned FIt-SNE directory (ie. '/path/to/dir/FIt-SNE') (required for using fftRtsne – only first time runTSNE is called) (default NULL). |
rand.seed |
Random seed for reproducibility (default 42). |
In order to run fftRtsne (recommended for large datasets), you must first install FIt-SNE as detailed here. Include the path to the cloned FIt-SNE directory as the fitsne.path parameter, though this is only necessary for the first call to runTSNE. For more detailed FIt-SNE installation instructions, see the liger repo README.
liger
object with tsne.coords slot set.
## Not run: # ligerex (liger object), factorization complete # generate H.norm by quantile normalizig factor loadings ligerex <- quantile_norm(ligerex) # get tsne.coords for normalized data ligerex <- runTSNE(ligerex) # get tsne.coords for raw factor loadings ligerex <- runTSNE(ligerex, use.raw = TRUE) ## End(Not run)
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