Hello All,
This may sound like a vague question but your help and inputs on this could really help me move forward. I am helping a bench scientist with his single cell RNA sequencing data generated using drop-seq platform. I did the basic QC analysis and everything seems to be fine with that. Then I performed clustering to find genes with similar expression profile, I did that by using seurat(http://satijalab.org/seurat/pbmc-tutorial.html). I'm almost done with the analysis and my t-SNE plot shows me 5 decent clusters. I guess at the end I would have to label each cluster by a cell type provided that a particular cell-type is known to express a marker-gene which might be a part of a cluster. Is there a universal list of cell-type gene marker that is available and could be applied with what I am doing? Please let me know if the question makes sense, I am trying to do something like the "Assigning cell type identity to clusters" section of the seurat tutorial(http://satijalab.org/seurat/pbmc-tutorial.html).
Update: Memory cells CCR7+/CD45RA- were used in the experiment and were extracted from blood.
3 answers
In my opinion annotating cell clusters using marker genes by hand is a massive pain and is very subjective. I used the SingleR package, which iteratively compares non-parametric gene expression profile correlations of your cells with annotated reference cells. It's very easy to set up and use and I've gotten pretty reliable results using it.
This might be an alternative and interesting to you for predicting marker genes from your dataset,
http://bioconductor.org/packages/release/bioc/vignettes/SC3/inst/doc/my-vignette.html
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Are you working on a specific tissue? Might be worth mentioning.
Thank you for your response. I have updated my post.