Unveiling new maps of biology with Squidpy

on YouTube ↗29m

" summary

Spatial transcriptomics gets practical: Squidpy is a Python library that loads Visium-style count matrices plus images, computes spatial statistics (Moran’s I), visualizes gene expression on mouse brain sections, segments cells and runs deconvolution pipelines. Claims include recovering anatomical regions from marker genes and handling spot-based data where each spot contains 5-10 cells. Remaining gaps are scalable I/O for terabyte experiments and robust cell-type deconvolution for mixed spots.

AI-written summary · about

" chapters (12)

1. 0:00Introduction
2. 1:08Biology and gene expression
3. 4:28Spatial transcriptomics importance
4. 6:57Acquiring spatial transcriptomics data
5. 9:56Spatial tech comparison
6. 12:3010x Visium workflow
7. 15:48Squidpy library
8. 19:46Spatial stats and segmentation
9. 20:50Cell type deconvolution challenges
10. 21:57Q&A
11. 25:58Community support and future
12. 27:03Foundation models for transcriptomics

" related talks

• 47mBANKSY: A Spatial Omics Algorithm that Unifies Cell Type Clustering and Tissue Domain SegmentationShyam Prabhakar · From Algorithms to Discovery in Genome-Scale Biology and Medicine 2022
• 25mBig Brains, Small Targets: Whole-Brain Image Analysis with PythonIshrat Zaman · PyCon AU 2025
• 20mCustom Python Applications in NeuroscienceSimon Salinas, Gagan Sharma · PyCon Australia 2015 Science/Data Miniconf
• 42mPython’s role in accelerating biomedical scienceLi Ting Chen · PyCon APAC 2019
• 35mMachine Learning for Single-Cell 3D EpigenomicsJian Ma · From Algorithms to Discovery in Genome-Scale Biology and Medicine 2022
• 47mPython for BioinformaticsClare Sloggett · PyCon Australia 2014 Science & Data miniconf
• 11mShweta Bhandare at StaffPlus London 2023Shweta Bhandare · StaffPlus London 2023
• 29mHarnessing Multimodal Single-Cell Sequencing Data for Integrative AnalysisElizabeth Purdom · Computational Challenges in Very Large-Scale 'Omics'