Tool:KNetL versus tSNE and UMAP for dimensionality reduction in single cell RNA-seq
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KNetL map (pronounced like "nettle") is a new dimensionality reduction developed for scRNA-Seq. It's capable of zooming and shows more detail than tSNE or UMAP.

To see more details: https://www.biorxiv.org/content/10.1101/2020.05.05.078550v1

KNetL map is available through iCellR package:

https://github.com/rezakj/iCellR (GitHub)

https://CRAN.R-project.org/package=iCellR (CRAN)

How to run KNetL, tSNE and UMAP using iCellR:

my.obj <- run.knetl(my.obj, dims = 1:20, k = 100)

my.obj <- run.pc.tsne(my.obj, dims = 1:10)

my.obj <- run.umap(my.obj, dims = 1:10)

Here we use a k value of 100, but this might not be ideal for your data.

Important Note:

  • Because KNetL has a very high resolution it's best to set the dims value to 20 (this usually works best for most data) and 10 for UMPA and tSNE.
  • In order to zoom, use the k value. For data with more than 5,000 cells use a k value of about 400. A k value of 400 usually works for large datasets, but you can adjust it for your intended resolution. Just like a microscope, you need to zoom in and out to see the intended amount of details.

KNetL compared to tSNE and UMAP

dimensionality reduction tSNE UMAP KNetL Tool • 611 views
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