I have two small single cell datasets containing RNASeq data from 12, and 20 cells respectively, which were manually isolated.
Our hope is to potentially project this data onto another, annotated scRNA-seq dataset which should contain these cells, to see where our data falls into the other dataset and hopefully do some differential expression against other celtypes.
However, the first thing I'd need to do is to combine the two aforementioned datasets, which were isolated and sequenced at different times, as well as at different depths, and I was wondering what the best way to combine these datasets was.
I have used Salmon (separately for each dataset) for the quantification, followed by tximport with the hopes of later using this data as a SingleCellExperiment or Seurat object, in order to make use of some projection functions.
I searched this forum and found these two posts which seem relevant to my question:
Would reading the data in from both salmon runs using tximport (with countsFromAbundance set to "lengthScaledTPM" as described here) and then using the txi$counts as the count matrix to create a SingleCellExperiment object, followed by limma batch correction be appropriate here?