Question: Single cell cluster annotation and validation tools: recommendations?
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gravatar for A248
6 months ago by
A2480
A2480 wrote:

Hi, I am working on a single-cell dataset, would you have any recommendations for tools/algos for the following two aspects

  1. After dimensionality reduction and cell clustering, we have annotated clusters based on general understanding of immunology (e.g. B cells annotated as such because they express MS4A1, CD79a strongly etc). But is there a way to compare quantitatively how well the transcriptional signatures of populations in the published literature (say of B cells, taken from bulk RNA seq) matches our cluster annotation as B cells? What would be the best algorithm for this "scoring"?

  2. We have carried out bulk RNA sequencing of certain sub-populations purified by flow cytometry. We have a list of top DEGs expressed by these purified populations. Is there a way to highlight the cells which express these DEGs on the single-cell dataset? (Using Seurat, we can light up cells expressing one gene. But how would we do the same for a list of genes?)

Many thanks for any suggestions!

ADD COMMENTlink modified 6 months ago by jared.andrews075.5k • written 6 months ago by A2480
3
gravatar for jared.andrews07
6 months ago by
jared.andrews075.5k
St. Louis, MO
jared.andrews075.5k wrote:
  1. SingleR is perfect for your first problem (full disclosure: I've been involved in its development). It can annotate your cell types based on purified bulk RNA-seq or single-cell datasets, eliminating the need for you to manually annotate based on a handful of marker genes for each cell type. It works quite well, is workflow agnostic, is very fast, and has a number of diagnostic visuals to help you determine whether to believe the assigned labels. It can annotate both individual cells and clusters and has several reference datasets (particularly of the immune variety) built-in.

  2. What I usually do in this case is to summarize the score for a list of genes and display that. The AddModuleScore function in Seurat will do that for you, you just need to feed it a list of genes.

ADD COMMENTlink written 6 months ago by jared.andrews075.5k
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