# Apply sc.pp.highly\_variable\_genes to SCT-normalized residuals or counts

**URL:** <https://discourse.scverse.org/t/apply-sc-pp-highly-variable-genes-to-sct-normalized-residuals-or-counts/1642>\
**Category:** scanpy\
**Created:** [July 27, 2023, 10:52pm UTC](https://discourse.scverse.org/t/apply-sc-pp-highly-variable-genes-to-sct-normalized-residuals-or-counts/1642 "2023-07-27T22:52:43Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![Holly](https://avatars.discourse-cdn.com/v4/letter/h/48db29/32.png) [@Holly](https://discourse.scverse.org/u/Holly)\
**Post date:** [July 27, 2023, 10:52pm UTC](https://discourse.scverse.org/t/apply-sc-pp-highly-variable-genes-to-sct-normalized-residuals-or-counts/1642/1 "2023-07-27T22:52:44Z")

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Can the scanpy team answer this questions?  
To integrate multiple datasets, I have applied SCT-normalization followed by harmony using Seurat. Then, I applied scanpy for the downstream analysis. After filtering out unwanted population, I want to selected HVG and redo the clustering. Now, the questions is that sc.experimental.pp.highly\_variable\_genes() expect raw counts (integer) which is not my case; while sc.pp.highly\_variable\_genes() has three _flavor_ [[Satija15]], [[Zheng17]], [[Stuart19]]. Which one should I apply?

Thank you,