BestPracticesST
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lmweber
'Best Practices for Spatial Transcriptomics Analysis with Bioconductor' online book
Currently in the [clustering](https://lmweber.org/BestPracticesST/chapters/clustering.html) chapter, we only have a short example using non-spatial clustering, and then list some alternatives for spatial clustering algorithms. @estellad We have had good experiences with...
Hi @estellad, thank you for getting in touch regarding adapting your workflow materials from the BC2 conference for inclusion in the book. As we discussed by email, I'm opening some...
Following on from discussion in #42 @estellad In this issue we are adding a workflow chapter using the Xenium dataset adapted from @estellad's BC2 workflow materials. This will also be...
Integrate discussion from @boyiguo1 on batch effects in multiple-sample datasets, possibly in a new section on analyses for multiple-sample datasets
Include some info on number of cells per spot for human brain / mouse brain tissue for sequencing-based / spot-based platforms
Add an introductory chapter with some additional details on scientific background / introductory material on the scientific context of SRT analyses. This will be helpful for new users / analysts...
Clarify QC on mitochondrial proportion (whether to use)
Link to Chapter: https://lmweber.org/OSTA-book/quality-control.html Suggestions: 1. Emphasize the column `cell_count` in the `SpatialExperiment` is a product of `VistoSeg` instead of `spaceranger count` to avoid confusion between counting the cells and...
QC chapter should include a short paragraph on filtering to retain only protein-coding genes. This is a useful standard filtering step in most datasets, although in some contexts / depending...