You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
seu <- FindSpatiallyVariableFeatures(seu, assay = "SCT", features = VariableFeatures(seu)[1:3000],
selection.method = "moransi")
Besides reducing the number of highly variable genes, what methods can be used to speed up computation?
The future package doesn't seem to be working.
library(future)
plan("multisession", workers = 8)
Computing Moran's I
|++++++++++++++++++++++++++++++++++++++++++++++++++| 100% elapsed=04m 17s
reacted with thumbs up emoji reacted with thumbs down emoji reacted with laugh emoji reacted with hooray emoji reacted with confused emoji reacted with heart emoji reacted with rocket emoji reacted with eyes emoji
Uh oh!
There was an error while loading. Please reload this page.
-
seu <- FindSpatiallyVariableFeatures(seu, assay = "SCT", features = VariableFeatures(seu)[1:3000],
selection.method = "moransi")
Besides reducing the number of highly variable genes, what methods can be used to speed up computation?
The future package doesn't seem to be working.
library(future)
plan("multisession", workers = 8)
Computing Moran's I
|++++++++++++++++++++++++++++++++++++++++++++++++++| 100% elapsed=04m 17s
Beta Was this translation helpful? Give feedback.
All reactions