vertesy/seurat.multicore

Multicore and utility functions for Seurat 2 & 3, using doMC / foreach packages.

seurat.multicore's Issues

FindAllMarkers.multicore does not reproduce FindAllMarkers

Tested in subset of data. Will reproduce

How to do subclustering the best?

Do you have to re identify variable genes?

• TLDR: unclear, probably start from scratch

it was asked here

Side note:

Running FindVariableGenes() and RunPCA() again on the integrated dataset does not seem helpful to me because the limited feature space of 3000 is not changed. The alternative would be to subset() the population of interest and run the complete preprocessing including integration only on those cells again. That enables to change the feature space.

How to re identify variable genes on integrated data?

We do not support the identification of variable features on integrated data. If you want to subset and recluster using a new set of variable genes, you need to switch the assay of the subsetted to the 'RNA' assay. [source]

→ → It was not done in the test I did.

Cell-free RNA correction (ambient RNA / the soup) seems to improve some datasets dramatically.

Effect

[source](http://dx.doi.org/10.1101/856476. )

Methods

• Empty drops as part of DropletUtils
• SoupX

summary

TO DO

• implement subset-bam

Support For Seurat 4.X

HI,

I appreciate if you could support multicore for Seurat v.4.x

Thanks.

color UMAP by genotype frequency

1. Ideally you calculate frequency in a raster like manner, with sub-cluster resolution.
2. Store in @meta and plot as usual, but change color gradient. (Viridis?)