single cell analysis

Question

[Mo]

Hello,

I have been trying to analysis a single cell data but faced lots of issue. could someone comment on this data?

Lets say I want to see the distribution of one specific gene named tP53 across all cell lines, how can I merge the annotation to the count?

https://github.com/czi-hca-comp-tools/easy-data/blob/master/datasets/tabula_muris.md#count-files-for-r

I basically cannot find how to annotate the data

library(tidyverse)

tm.droplet.matrix = readRDS("TM_droplet_mat.rds")
tm.droplet.metadata = read_csv("TM_droplet_metadata.csv")

but then it becomes fuzzy for me how to get them merged and then try to locate the TP53 and then check the distribution.

[rpolicastro]

For analysis of single-cell data in R you want to load your data into either a SingleCellExperiment or Seurat object.

See OSCA for more info.

library("scran")

sce <- SingleCellExperiment(list(counts=tm.droplet.matrix))

metadata <- as.data.frame(tm.droplet.metadata)
rownames(metadata) <- metadata$cell
colData(sce) <- cbind(colData(sce), metadata)

See the Seurat website for more info.

library("Seurat")

metadata <- as.data.frame(tm.droplet.metadata)
rownames(metadata) <- metadata$cell

seu <- CreateSeuratObject(tm.droplet.matrix, meta.data=metadata)

[Mo]

rpolicastro are you able to tell me how to do PCA of a given gene using this data? or get a smaller size of the data so that I can try to understand the structure?

I basically want to know the changes of TP53 , are you able to give me a direct link to Seurat or the other package?

Thanks