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demo/csama.qmd

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## CSAMA
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### preamble
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In this demo, we'll be analyzing 5K-plex Xenium (10x Genomics)
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data on a tissue section from a human breast cancer biopsy,
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derived from [here](https://www.10xgenomics.com/datasets/xenium-prime-ffpe-human-breast-cancer).
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These include the following elements:
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- two `image`s (histology and immunofluorescence)
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- two `shape`s (nuclei and membrane boundaries)
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- one `table` (gene $\times$ cell data)
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- one `point` (RNA transcripts)
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A size-reduced example dataset has been deposited on Zenodo.
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We'll first retrieve the compressed *.zarr* store programatically,
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decompress it, and stash the data's on-disk file path for later:
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```{r load-zarr}
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# retrieve .zarr store from the web
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url <- "https://zenodo.org/records/20083116/files/BC_xenium_sdata_lowres.zarr.zip?download=1"
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zip <- tempfile("sd", fileext=".zarr.zip")
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download.file(url, zip, quiet=TRUE)
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# decompress, stash & view contents
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nm <- unzip(zip, exdir=dirname(zip))
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zs <- grepv("zarr$", dirname(nm))
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```
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```{r show-zarr, echo=FALSE}
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htmltools::pre(
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style="max-height:400px; overflow-y:auto;",
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paste(capture.output(fs::dir_tree(zs, recurse = 2)), collapse="\n"))
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```
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### dependencies
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```{r load-libs, message=FALSE, warning=FALSE}
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library(sf)
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library(SingleCellExperiment)
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```
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### data
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A size-reduced example dataset has been deposited on Zenodo.
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We'll first retrieve the compressed *.zarr* store programatically,
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decompress it, and stash the data's on-disk file path for later:
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```{r load-zarr}
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url <- "https://zenodo.org/records/20083116/files/BC_xenium_sdata_lowres.zarr.zip?download=1"
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zip <- tempfile("sd", fileext=".zarr.zip")
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download.file(url, zip, quiet=TRUE)
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nm <- unzip(zip, exdir=dirname(zip))
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zs <- grepv("zarr$", dirname(nm))
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basename(zs)
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```
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### setup
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We can instruct our session to use an existing environment with our Python

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