Package index

All functions

ImageArray() data(<ImageArray>) dim(<ImageArray>)

The `ImageArray` class

LabelArray() dim(<LabelArray>) `[`(<LabelArray>,<ANY>,<ANY>,<ANY>)

The `LabelArray` class

PointFrame() names(<PointFrame>) dim(<PointFrame>) length(<PointFrame>) `$`(<PointFrame>) `[[`(<PointFrame>,<ANY>,<ANY>) `[`(<PointFrame>,<missing>,<ANY>,<ANY>) `[`(<PointFrame>,<ANY>,<missing>,<ANY>) `[`(<PointFrame>,<missing>,<missing>,<ANY>) `[`(<PointFrame>,<numeric>,<numeric>,<ANY>) as.data.frame(<PointFrame>)

The `PointFrame` class

ShapeFrame() dim(<ShapeFrame>) length(<ShapeFrame>) names(<ShapeFrame>) `$`(<ShapeFrame>) `[`(<ShapeFrame>,<missing>,<ANY>,<ANY>) `[`(<ShapeFrame>,<ANY>,<missing>,<ANY>) `[`(<ShapeFrame>,<missing>,<missing>,<ANY>) `[`(<ShapeFrame>,<numeric>,<numeric>,<ANY>)

The `ShapeFrame` class

SpatialData() `$`(<SpatialData>) data(<SpatialDataElement>) meta(<SpatialDataElement>) images(<SpatialData>) labels(<SpatialData>) shapes(<SpatialData>) points(<SpatialData>) tables(<SpatialData>) imageNames(<SpatialData>) labelNames(<SpatialData>) shapeNames(<SpatialData>) pointNames(<SpatialData>) tableNames(<SpatialData>) image(<SpatialData>) label(<SpatialData>) shape(<SpatialData>) point(<SpatialData>) table(<SpatialData>) `[[<-`(<SpatialData>,<numeric>,<ANY>,<ANY>) `[[<-`(<SpatialData>,<character>,<ANY>,<ANY>) `images<-`(<SpatialData>,<list>) `labels<-`(<SpatialData>,<list>) `shapes<-`(<SpatialData>,<list>) `points<-`(<SpatialData>,<list>) `tables<-`(<SpatialData>,<list>) `image<-`(<SpatialData>,<character>,<ImageArray>) `label<-`(<SpatialData>,<character>,<LabelArray>) `point<-`(<SpatialData>,<character>,<PointFrame>) `shape<-`(<SpatialData>,<character>,<ShapeFrame>) `table<-`(<SpatialData>,<character>,<SingleCellExperiment>) `image<-`(<SpatialData>,<numeric>,<ImageArray>) `label<-`(<SpatialData>,<numeric>,<LabelArray>) `point<-`(<SpatialData>,<numeric>,<PointFrame>) `shape<-`(<SpatialData>,<numeric>,<ShapeFrame>) `table<-`(<SpatialData>,<numeric>,<SingleCellExperiment>) `image<-`(<SpatialData>,<missing>,<ImageArray>) `label<-`(<SpatialData>,<missing>,<LabelArray>) `point<-`(<SpatialData>,<missing>,<PointFrame>) `shape<-`(<SpatialData>,<missing>,<ShapeFrame>) `table<-`(<SpatialData>,<missing>,<SingleCellExperiment>) `image<-`(<SpatialData>,<ANY>,<NULL>) `label<-`(<SpatialData>,<ANY>,<NULL>) `shape<-`(<SpatialData>,<ANY>,<NULL>) `point<-`(<SpatialData>,<ANY>,<NULL>) `table<-`(<SpatialData>,<ANY>,<NULL>) `image<-`(<SpatialData>,<ANY>,<ANY>) `label<-`(<SpatialData>,<ANY>,<ANY>) `shape<-`(<SpatialData>,<ANY>,<ANY>) `point<-`(<SpatialData>,<ANY>,<ANY>) `table<-`(<SpatialData>,<ANY>,<ANY>)

The `SpatialData` class

Zattrs() `$`(<Zattrs>) axes(<Zattrs>) coordTransData(<Zattrs>) coordTransName(<Zattrs>) coordTransType(<Zattrs>) axes(<SpatialDataElement>) coordTransData(<SpatialDataElement>) coordTransName(<SpatialDataElement>) coordTransType(<SpatialDataElement>)

The `Zattrs` class

available_10x_xen_zips()

use 'paws::s3' to interrogate an NSF Open Storage Network bucket for zipped 10x-produced Xenium outputs

available_sdio()

enumerate modules

available_spd_zarr_zips()

use 'paws::s3' to interrogate an NSF Open Storage Network bucket for zipped zarr archives for various platforms

blobs

`SpatialData` .zarr toy datasets

.coord2graph()

CS graph representation

do_tx_to_ext()

Use Python's 'spatialdata' 'transform_to_data_extent' on a spatialdata zarr store

.guess_scale()

#' @rdname ImageArray #' @exportMethod [ setMethod("[", "ImageArray", \(x, i, j, k, ..., drop=FALSE) # TODO: subsetting for multiscales if (missing(i)) i <- TRUE if (missing(j)) j <- TRUE if (missing(k)) k <- TRUE # get scale factor between pyramid layers is <- seq_along(x@data) as <- lapply(is, \(.) data(x, .)) ds <- vapply(as, dim, numeric(3)) sf <- if (length(is) == 1) 1 else cumprod(vapply( is[-1], \(.) ds[,.]/ds[,.-1], numeric(3))[, 1]) # validity if (isTRUE(j)) j <- seq(ds[2,1]) if (isTRUE(k)) k <- seq(ds[3,1]) # for (. in seq_along(ij <- list(j=j, k=k))) # if ((ds[.+1,1] # max(ij[[.]]) # stop("invalid '", names(ij)[.], "'") for (. in seq_along(sf)) .j <- if (!isTRUE(j)) unique(ceiling(j*sf[.])) else j .k <- if (!isTRUE(k)) unique(ceiling(k*sf[.])) else k x@data[[.]] <- data(x, .)[i, .j, .k, drop=FALSE] return(x) )

.get_path()

get transformations path

mask

Masking

merfish_demo_path()

check cache for merfish.zarr.zip and return path; retrieve/stash/return path if not found

show(<SpatialData>) show(<ImageArray>) show(<LabelArray>) show(<PointFrame>) show(<ShapeFrame>)

Miscellaneous `Miro` methods

path_to_10x_xen_demo()

provide path to a zip file from 10x genomics for Xenium platform

plotSpatialData() plotImage(<SpatialData>) plotLabel(<SpatialData>) plotPoint(<SpatialData>) plotPoint(<PointFrame>) plotShape(<SpatialData>)

`SpatialData` visualization

query(<SpatialData>) query(<ImageArray>) query(<LabelArray>) query(<ShapeFrame>) query(<PointFrame>)

spatial queries

readImage() readLabel() readPoint() readShape() readTable() readSpatialData()

Reading `SpatialData`

spd_demo_cached_path()

check cache for demonstration .zarr.zip and return path; retrieve data, cache it, return path if not found

spdzPath()

obtain path to cached zip archive of SpatialData zarr

unzip_merfish_demo()

unzip cached merfish demo data to specified folder

unzip_spd_demo()

unzip selected demo data to specified folder

use_sdio()

Use Python's 'spatialdata-io' to transform manufacturer output to .zarr with specific folder structure.