6. DEA

We continue the Seurat tutorial on the analysis of Peripheral Blood Mononuclear Cells (PBMC) at the Finding differentially expressed features step.

What is the statistical test performed by the FindMarkers function ?

Which statistical test would you choose given your knowledge of the data ?

Given the nature of the data, which other statistical tests could you use ?

##             p_val avg_log2FC pct.1 pct.2    p_val_adj
## IL32 2.593535e-91  1.3221171 0.949 0.466 3.556774e-87
## LTB  7.994465e-87  1.3450377 0.981 0.644 1.096361e-82
## CD3D 3.922451e-70  1.0562099 0.922 0.433 5.379250e-66
## IL7R 1.130870e-66  1.4256944 0.748 0.327 1.550876e-62
## LDHB 4.082189e-65  0.9765875 0.953 0.614 5.598314e-61

What is the difference between the p_val column and the p_val_adj column ?

# you can plot raw counts as well
VlnPlot(pbmc, features = c("NKG7", "PF4"), slot = "counts", log = TRUE)

What can you say about the distribution of the DE gene ?

We will comeback on DEA after the next section about pseudo-time in scRNASeq analysis.