Goals:
We want to identify cell states specific to certain stages of disease. To do this we run enrichment analysis on consecutive subsets of disease severity.
Cases where low IFN states are enriched more than high IFN states:
For high IFN cell subtypes, lower IFN subsets are more enriched in later stages of disease, possibly indicating that at these stages the peak of IFN response is past.
In asymp and mild disease we see an enriched population of CD8+ T cells with very low IFN expression, while IFN activated states are enriched in later stages of disease
Cell states differentially enriched between stages e.g. B naive cell subsets specific to mild disease
Is Nhood cell abundance predictive of stage of disease/time since onset?
To do:
Functional annotation of B naive subsets and CD8+T cell subsets:
[x] package DE analysis functions (ideally to run in farm): for each cell type split nhoods in early_enriched/late_enriched/other (subsets present in healthy cells), split DEs as up in both or up in one
[x] gseapy analysis on significant genes (up in one)
[ ] Are these 2 subsets identified in PC design or with other uncertainty metrics?
[ ] Should I do the milo test by lineage? With a new KNN graph for each lineage?
Goals: We want to identify cell states specific to certain stages of disease. To do this we run enrichment analysis on consecutive subsets of disease severity.
Cases where low IFN states are enriched more than high IFN states:
Cell states differentially enriched between stages e.g. B naive cell subsets specific to mild disease
Is Nhood cell abundance predictive of stage of disease/time since onset?
To do:
Functional annotation of B naive subsets and CD8+T cell subsets: