In vondoRishi/scpackages: scpackages has many single-cell R and python packages to use them easily.

```{css, echo=FALSE} .scroll-100 { max-height: 400px; overflow-y: auto; background-color: inherit; }

# Clustering 
## Highly variable features

```r
obj_scRNA@misc$hvgPlot

Show/Hide List of selected variable genes.

x <- VariableFeatures(object = obj_scRNA)
print(x)

Cell cycle

Loading on PC

Are principal component loaded with cell cycle genes?

obj_scRNA@misc$CC_pca_bar

Before regressing out

obj_scRNA@misc$before_cc_pca

After regressing out

obj_scRNA@misc$after_cc_pca 

Cluster

Pca analysis

obj_scRNA@misc$elbowPlot

0,0Max r obj_scRNA@misc$maxPca principal component and resolution r obj_scRNA@misc$resolution selected.

Dimensional reduction

obj_scRNA@misc$umapPlot
if(!is.null(obj_scRNA@misc$markers_info) ){
  # DT::datatable(round_df(obj_scRNA@misc$markers_info,digits = 6), rownames = FALSE)
  DT::datatable(obj_scRNA@misc$markers_info, rownames = FALSE)
}else{
  print("Cluster markers are not found")
}

Command History

Show/Hide List of selected variable genes.

obj_scRNA@commands

Session Info

Show/Hide List of selected variable genes.

sessionInfo()

vondoRishi/scpackages documentation built on Feb. 27, 2020, 1:52 a.m.