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BayesSpace

 BayesSpace

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

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Leonardo Collado-Torres

October 22, 2020
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  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?