Pre-processing and filtering CITE-Seq data

Help scvi-tools
1

The scvi-tools tutorials datasets are pre filtered to eliminate doublets and low-quality cells and genes as detailed in the TotalVI paper. Can scvi-tools can be used to filter data sets?

I used Seurat in RStudio to clean up my data set to get rid of doublets, cells with < 200 genes, and cells with high mitochondrial and ribosomal RNA. I tried to convert the Seurat object into a h5ad file that I can open in Spyder (Python 3.8) but this file was not recognizable by scvi-tools.

What is the best way to filter the data easily (I find Seurat easy to use) and then use scvi-tools for analyses and figures?

##Export and use python tools
library(Seurat)
library(SeuratData)
library(SeuratDisk)

SaveH5Seurat(data, filename = “filtered-data.h5ad”)
Convert(“filtered-data.h5ad”, dest = “h5ad”)

2

Conversion can indeed be tricky, especially in the CITE-seq case. I believe the code shared here might have a bug and need to be as follows:

SaveH5Seurat(data, filename = “filtered-data.h5seurat”)
Convert(“filtered-data.h5seurat”, dest = “h5ad”)

But you can always also save everything in csv format and load into python separately.