Open Ruismart opened 5 months ago
After getting more familiar with the method/code, I think it might be not easy (like, linearly) to label back source-genes/PCs on final tPCs through the distance matrix. I have been trying to think about another way to do the calculation considering pre- feature selection could really make a huge contribute to final trajectories.
Hi Denis,
Thanks for the beautiful tool tSPACE, I have been trying to use it to build reasonable trajectories for a bunch of developmental single cell data. Here I have got some issue:
So my question is: if there is a way to extract the tPC formula, as getting PCA coefficient from seur.obj@reductions$PCA@feature.loadings ? Then I could run tSPACE on a standard and relatively small dataset at first, then extract the formula for each tPC, after that, I could do the calculation using those pre-built tPC-formulas on any new and bigger datasets with similar celltypes and same pre-normalization.
Kind Wishes,
Shaorui