# Looking for Pseudobulk Methods

**URL:** <https://discourse.scverse.org/t/looking-for-pseudobulk-methods/3341>\
**Category:** General\
**Created:** [November 16, 2024, 3:15pm UTC](https://discourse.scverse.org/t/looking-for-pseudobulk-methods/3341 "2024-11-16T15:15:09Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![victorsanchezarevalo](https://yyz1.discourse-cdn.com/flex035/user_avatar/discourse.scverse.org/victorsanchezarevalo/32/1228_2.png) [@victorsanchezarevalo](https://discourse.scverse.org/u/victorsanchezarevalo)\
**Post date:** [November 16, 2024, 3:15pm UTC](https://discourse.scverse.org/t/looking-for-pseudobulk-methods/3341/1 "2024-11-16T15:15:09Z")

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I’m exploring new ways to generate pseudobulk data that better reflect biological reality. Most approaches I’ve found in the literature, or in commonly used packages, rely on simply summing or averaging single-cell expression data.

Any insights or recommendations would be greatly appreciated! 🙏✨

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**Author:** ![gtca](https://yyz1.discourse-cdn.com/flex035/user_avatar/discourse.scverse.org/gtca/32/1199_2.png) [@gtca](https://discourse.scverse.org/u/gtca)\
**Post date:** [November 17, 2024, 4:53pm UTC](https://discourse.scverse.org/t/looking-for-pseudobulk-methods/3341/2 "2024-11-17T16:53:52Z")

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Hey @victorsanchezarevalo,

Counting reads / fragments for cell populations rather than individual cells seems like a fairly reasonable approach.  
Another option is metacells, e.g. see [SEACells](https://www.nature.com/articles/s41587-023-01716-9) as one of the implementations.