tSNE and UMAP of scATAC-seq data looks like spaghetti
I would like to use R to generate cluster my 20k cells from a single cell ATAC-seq experiment.
I ran PCA then selected the first 50 components, which were put into tSNE's normalize_input() then Rtsne(). This is the result I get.
I tried multiple perplexities from 5 to 50, number of components from 20 to 200, and UMAP. However the results were roughly the same.
Do you know what could cause this? I did not filter out peaks before running this because I am not sure what cutoff to use.
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For UMAP try to increase negative_sample_rate to 25 or 50; For t-SNE try to use much large perplexity, e.g. 1000.
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Show your full code or we're just going to be guessing at what you did. I'd recommend using a framework meant for scATAC analysis like ArchR or Signac.
Thanks Jared! I will use one of those to generate a tsne rather than troubleshooting. Here is my code.
I strongly recommend to follow a guided tutorial and use a dedicated package as mentioned above.
Points that may miss here:
For single-cell RNA-seq I follow https://bioconductor.org/books/release/OSCA/ but I have no hands-on with scATAC-seq so far. I guess just following
ArchRorSignacvignettes will save you a lot of trouble.Have you tried normalizing the data before PCA?