Perform tsne using bias corrected deviations to visualize either cell/sample similarity or motif/kmer/annotation similarity
deviationsTsne(object, threshold = 1.5, perplexity = if (what == "samples") 30 else 8, max_iter = 1000, theta = 0.5, what = c("samples", "annotations"), shiny = FALSE)
| object | deviations result |
|---|---|
| threshold | variability threshold -- use only deviations with variability greater than threshold |
| perplexity | perplexity parameter for tsne |
| max_iter | max iterations parameter for tsne |
| theta | theta parameter for tsne |
| what | tsne for similarity of samples or annotations? |
| shiny | load a shiny widget that enable you to explore perplexity and variability threshold parameter? |
data.frame with two columns for the two dimensions of tSNE output
# NOT RUN { # Load very small example results from computeDeviations data(mini_dev, package = "chromVAR") tsne_res <- deviationsTsne(mini_dev, threshold = 0.8, shiny = FALSE) # setting very low variabilitiy threshold because this is mini data set # threshold should generally be above 1 # Use plotVariability to get a sense of an appropriate threshold # }