shuang1330 / single_cell Goto Github PK

Implement and benchmark different pseudo time orderings:

• Plot PAGA in same dimension (of the UMAP)
• Test other gene selections: all DE genes (not only 0-3h) and most variable genes
• Test MST Algorithms / Slingshot
• Smaller PCs
• Send UMAP on Monocytes 1 and calculated pseudo time (anndata object) to Katharina for RNA velocity

New open issues:

• Calculate correlation on Blueprint data (Spearman & Rho)

• Repeat pseudo time & RNA velocity analysis with other pathogenes (and cell types)

• Test WOT (waddington optimal transport)

• Test bbknn correction of data

• Test correlation for different time points

• Define a project outline

• Start with correlation QTLs (think about targeted approach)

Next meeting next Monday (05-10).

Perform RNA velocity on the data set:

• Update presentation: one slide with gene selection problem and one with results for Monocytes
• Test RNA velocity with only DE genes (or some other selected subset?)
• Compare RNA velocity with pseudo time results

Different correlation metrics for single cell data shall be applied and evaluated. The current open points are:

• Calculate correlation with gene network data - blood (Shuang)
• Save correlation matrix from rho object separately to save memory (Dylan)
• Implement spearman correlation on single cell data & compare it with rho (Dylan)
• Compare correlation with String data base and add plots to presentation (Katharina)
• Transfer Blueprint data to gearshift (Katharina)