Five visualizations of pyscenic transcription factor analysis results,

Transcription factor analysis of pyscenic showed that each single cell subgroup specifically activated transcription factors.

See the previous article:

Transcription factor analysis and data visualization of pySCENIC (1)

Transcription factor analysis and data visualization of pyscenic (Ⅱ)

This content mainly focuses on the specific activation of transcription factors and the visualization of each single cell subgroup. First, review the transcription factor analysis results of pyscenic again.

It is worth mentioning that in this pbmc3k data set, there are actually 220 transcription factors in more than 2,000 cells (208 in Ceng Laoshi's tutorial).

Look at the average transcription factor activity of different single cell subsets.

A strange thing happened here. At first we used phe atmap: pheatmap (regression _ by group _ scaled), so we wrote error: pheatmap (regression _ by group _ scaled): na/nan argument in pheatmap.

It can be seen that each single cell subgroup is indeed an activated transcription factor with its own specificity.

However, the SCENIC software package itself provides a calcRSS function to help us choose transcription factors specific to each single cell subgroup, which is called the rule of calculating specific scores.

References: RSS was first used by Suo et al. in Revealing the Key Regulators of Cell Characteristics in Mouse Cell Atlas. Mobile phone report (20 18). . doi: 10. 10 16/j . celrep . 20 18. 10.045

Running is super simple.

PAX5(+) and REL(+) are indeed highly expressed in B cells.

Sd.2 of df can also be calculated according to sd.

Or calculate sd.2 of df by the mean.

At this point, the course of transcription factor analysis and data visualization of pySCENIC is over, thanks to Ceng Laoshi and Shengxin Skill Tree.