Analyzing single cell RNA seq with multiple samples and conditions

Question

[biotrekker]

Hello all, I don't know if this is the appropriate place to ask to this question, but I am currently analyzing a single cell rna-seq dataset with 2 conditions and 10 samples each (total of 20 samples). The samples are not technical replicates, they come from different humans each. The files, once downloaded, are in .H5 format. After scouring the web, I still cannot find a pipeline that works for me. Should I analyze each of the samples individually or merge them into one some way and proceed? I am trying to follow the Seurat pipeline line so any help on that note would be helpful. I have written this code:

h5_files<-list.files(pattern ="*.h5") 
h5_read <- lapply(h5_files, Read10X_h5)
h5_seurat <- lapply(h5_read, CreateSeuratObject, min.cells=5, min.features=250, project="ccc") 

here h5_seurat in the last line of code is a list with 20 Seurat objects (from the original .H5) files. I want to follow the rest of the Seurat pipeline, but I don't know if should do it individually for each of the 20 samples or merge them somehow?

Thanks

Answer 1

[Rafael Soler]

Hello,

You can merge all the files into a Seurat object and continue the analysis with it. Here's an example similar to what you're looking for scRNA-seq example.

Best,

Rafael

[biotrekker]

Thanks for your help! Just to make sure (1) Is merging okay for .H5 type files and (2) here it suggests that merging samples is not a good idea unless samples are technical replicates and/or presumed batch effect is really low: The difference between merge and integration with Seurat objects I don't know if this applies to me?

Thanks

[Rafael Soler]

Hello,

When I was talking about "merge", I meant putting all the samples into the same R object. If you want to merge 2 samples reads into only 1, I wouldn't recommend it unless they are technical replicates.

Best,

Rafael