I have been desperately trying to analyze this single cell GEO accession or this one with various methods
I have tried the PIVOT package for R, which can use CSV files (available at this GEO accession, with bar codes as columns and genes in the rows) to analyze scmRNA, but apparently the files are too large for it to handle.
So I tried following this scanpy tutorial and I immediately got stuck, because its input is a .mtx file.
I attempted to use Cerebro, which is made for non coders but it requires a .crb or .rds file as input. There are no files like that in the first dataset, and multiple files in the second (while Cerebro only loads one).
So, honestly, I don't even know what to ask. Any solution for whichever method is welcome
GSE150728_RAW.tar(click CUSTOM to see the content) provides count matrices in RDS format which is a compessed sstorage format from R which can be loaded into R with
readRDS. This is probably raw counts, and with this you can use any of the usual packages to start analysis, be it Seurat, scran etc. If you have no background in the field then be careful though, scRNA-seq is imho one of the more-difficult-to-analyze NGS assays both in terms of complexity and also simply the size of the generated outputs.