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RNA velocity analysis component #5

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@LuckyMD

Description

@LuckyMD

Components needed for RNA velocity analysis and visualization inclusion into open pipelines:

  1. QC:
    function:
    scv.utils.show_proportions(adata)
  • just to see if data has sufficient unspliced counts
  1. Preprocessing and fit:
    functions:
    scv.pp.filter_and_normalize(adata, min_counts=20, min_counts_u=10)
    scv.pp.moments(adata)
    scv.tl.recover_dynamics(adata)

  2. QC2: Gene likelihood check:

  • this is manual so far...
  • some function on: adata.var[‘fit_likelihood’]
  • assessment (distribution plot, table for certain cutoffs)
  • potentially look at phase portraits of potential velocity genes
  • set adata.var['velocity_genes’] as mask on adata.var[‘fit_likelihood’]
  1. Velocity calculation step 2:
    function:
    scv.tl.velocity(adata, mode=‘dynamical’)
  • other modes possible, but this is probably best
  1. Velo visualization calculation:
    functions:
    scv.tl.velocity_embedding(adata, basis=‘umap’)
  • other bases possible, like diffmap, phate, etc)
  1. Velocity visualization plotting:
    function(s):
    scv.pl.velocity_embedding(adata, basis=‘umap’, color=, arrow_size=2, arrow_length=5, alpha=0.2, size=20)
  • also other plots like velocity_embedding_grid or velocity_embedding_stream
  • should combine into 1 visualization component ideally

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