BayesSpace

spatialLIBD journal club presentation on BayesSpace's pre-print available from https://www.biorxiv.org/content/10.1101/2020.09.04.283812v1

Transcript

1. BayesSpace Leonardo Collado Torres lcolladotor.github.io 2020-10-22
2. LIEBER INSTITUTE for BRAIN DEVELOPMENT https://twitter.com/raphg/status/1318244963927289857?s=20
3. LIEBER INSTITUTE for BRAIN DEVELOPMENT https://www.biorxiv.org/content/10.1101/2020.09.04.283812v1.article-metrics
4. LIEBER INSTITUTE for BRAIN DEVELOPMENT Resources • Pre-print: https://www.biorxiv.org/content/10.1101/2020.09.04.283812 v1 ◦ Has 2 supplementary files • Bioconductor package ◦ http://bioconductor.org/packages/BayesSpace ◦ https://github.com/edward130603/BayesSpace ◦ https://edward130603.github.io/BayesSpace/ • Processing code: https://github.com/msto/spatial-datasets
5. LIEBER INSTITUTE for BRAIN DEVELOPMENT 2 main features: enhanced clustering + sub-spot level analysis
6. LIEBER INSTITUTE for BRAIN DEVELOPMENT Main logical/processing steps: expression → PCs → sub-spot level modeling → high res PCs→ predicted expression
7. LIEBER INSTITUTE for BRAIN DEVELOPMENT Main parameter: number of clusters. Can be derived from the data too
8. LIEBER INSTITUTE for BRAIN DEVELOPMENT Figure 7 from our pre-print https://www.biorxiv.org/content/10.1101/2020.02.28.969931v1.full.pdf
9. LIEBER INSTITUTE for BRAIN DEVELOPMENT Remembering ARI: from our pre-print https://www.biorxiv.org/content/10.1101/2020.02.28.969931v1.full.pdf
10. LIEBER INSTITUTE for BRAIN DEVELOPMENT Figure 2: they do a better job! ^^
11. LIEBER INSTITUTE for BRAIN DEVELOPMENT Figure S1: their w i point towards outliers
12. LIEBER INSTITUTE for BRAIN DEVELOPMENT Some notes: positive and not so positive • Bioconductor-friendly • Will be a part of Bioconductor 3.12 • We can **use** it • BayesSpace (right now) is only meant for 1 image at a time • How long does it take to run? • Their analysis code is actually not public (or I haven’t found it) >.<
13. LIEBER INSTITUTE for BRAIN DEVELOPMENT Figure 3: can use marker genes & get some profiles at sub-spot level
14. LIEBER INSTITUTE for BRAIN DEVELOPMENT Figure 4: works for other tissue organizations too (non-laminar) & when you don’t know the number of clusters (q)
15. LIEBER INSTITUTE for BRAIN DEVELOPMENT Figure 5: sub-spot level model works with simulated data (from their own model)
16. LIEBER INSTITUTE for BRAIN DEVELOPMENT Figure S5: choosing the number of PCs is important too. Here they use PCs 1-7 for melanoma, 1-15 for DLPFC. Check outliers, think about computing time vs biology.
17. LIEBER INSTITUTE for BRAIN DEVELOPMENT stLearn Uses deep learning on images https://stlearn.readthedocs.io/ en/latest/stSME_clustering.ht ml#Human-Brain-dorsolateral- prefrontal-cortex-(DLPFC)
18. LIEBER INSTITUTE for BRAIN DEVELOPMENT Some questions • Will stLearn improve with improved images? • How sure are we that w i captures outliers? • How much will it be affected by artifacts? ◦ Can we use it to QC spots? ◦ If we drop spots, can we still run sub-spot? My guess: yes • How would you apply it to all 12 DLPFC images?