updated / repo being maintained

[kenneditodd]

Hello,

I would love to use this repo to help with my single cell annotation. It seems it is no longer being maintained. I have tried to run some things manually but all the data download links are broken. @olgabot is there any hope to see updates?

[olgabot]

Hi @kenneditodd, glad to hear this repo is useful to you! Unfortunately, I am no longer @czbiohub-sf and don't have permission to make any changes. Can you specify more what you're trying to do with the annotation? At this point, the publication is >5 years old, and doesn't use current state-of-the art tools.

Could you use the Tabula Muris Senis dataset hosted on CELLxGENE? Tabula Muris Senis is a superset of Tabula Muris -- it includes all the 3 month old mice from Tabula Muris, plus 1-month, 18-month, 21-month, 24-month, and 30-month old mice. The data "should" also be available on AWS here: https://registry.opendata.aws/tabula-muris-senis/

Hope that helps!

[kevynjackson]

Hi,

I have found a solution. The objects from the 2018 paper are in seurat v2 form and this is not compatible with v4 or v5 format. This code below worked for me:

load seurat

library("Seurat")

first load the old object

load("pathtodatafromfigshare_exampleforspleen/facs_Spleen_seurat_tiss.Robj")

Step 1: Extract data from Seurat v2 object

raw_counts <- [email protected]
normalized_counts <- tiss@data
scaled_counts <- [email protected]
metadata <- [email protected]

Step 2: Create a new Seurat v4/v5 object

tiss_v4 <- CreateSeuratObject(counts = raw_counts, meta.data = metadata)

Step 3: Add the normalized and scaled data

tiss_v4 <- SetAssayData(tiss_v4, slot = "data", new.data = normalized_counts)
tiss_v4 <- SetAssayData(tiss_v4, slot = "scale.data", new.data = scaled_counts)

Step 4: Transfer dimensionality reductions (if applicable)

if (!is.null(tiss@dr$pca)) {
tiss_v4[["pca"]] <- CreateDimReducObject(embeddings = tiss@dr$[email protected],
loadings = tiss@dr$[email protected],
key = "PC_",
assay = "RNA")
}

if (!is.null(tiss@dr$tsne)) {
tiss_v4[["tsne"]] <- CreateDimReducObject(embeddings = tiss@dr$[email protected],
key = "tSNE_",
assay = "RNA")
}