Package 'VisiumIO'

Compare barcodes between raw and filtered data

Description

This function compares the barcodes between raw and filtered data depending on the order of processing. Typically, the "raw" barcodes are compared to the "filtered" ones. The presence of raw barcodes in the filtered data are marked as TRUE in the resulting data.frame.

Usage

compareBarcodes(
  from_resource,
  to_resource,
  spacerangerOut,
  format = c("mtx", "h5"),
  processing = c("raw", "filtered"),
  ...
)

Arguments

from_resource	character(1) The path to the resource file whose barcodes are used as the basis of the comparison; typically, the "raw" feature barcodes are used.
to_resource	character(1) The path to the resource file whose barcodes are compared to the from_resource; typically, the "filtered" feature barcodes.
spacerangerOut	character(1) A single string specifying the path to the directory where the output of ⁠spaceranger count⁠ is located; typically (but not necessarily), this is the outs directory. The directory must contain the ⁠(processing)_feature_bc_matrix⁠ and spatial sub directories.
format	The format of the output. If missing and con is a file name, the format is derived from the file extension. This argument is unnecessary when con is a derivative of BiocFile.
processing	character(2) A vector of length 2 that corresponds to the processing type. The processing types are typically "raw" and "filtered". These are the prefixes of the folder names raw_feature_bc_matrix and filtered_feature_bc_matrix. The order of the vector determines the comparison. By default, processing = c("raw", "filtered"), which means barcodes in the raw data are compared to the filtered data.
...	Additional arguments passed to TENxH5 or TENxFileList.

Value

A data.frame with barcodes of the first element in the processing data type as the first column and a logical vector indicating whether the barcodes are found in the second element in processing. For example, if processing is c("raw", "filtered"), then the first column will be the barcodes in the raw data and the second column will be a logical vector indicating whether the barcodes are found in the filtered data.

Examples

if (interactive()) {
    compareBarcodes(
        from_resource = "V1_Adult_Mouse_Brain_raw_feature_bc_matrix.tar.gz",
        to_resource =
            "V1_Adult_Mouse_Brain_filtered_feature_bc_matrix.tar.gz",
    )

    compareBarcodes(
        from_resource =
            "V1_Adult_Mouse_Brain_raw_feature_bc_matrix.h5",
        to_resource =
            "V1_Adult_Mouse_Brain_filtered_feature_bc_matrix.h5"
    )

    compareBarcodes(spacerangerOut = "~/data/outs", format = "h5")

    compareBarcodes(
        spacerangerOut = "~/data/feature_bc_matrix", format = "mtx"
    )

    compareBarcodes(
        spacerangerOut = "~/data/folder_feature_bc_matrix", format = "mtx"
    )
}

---

Flip the Y-axis of cell or nucleus segmentations to align with H&E image

Description

This function flips the Y-axis of cell or nucleus segmentations stored in an sf object to align with the H&E image. The Y-axis flipping is necessary because the origin (0,0) in image coordinates is at the top-left corner, while in Cartesian coordinates, the origin is at the bottom-left corner. The function takes into account the image height and scaling factor to accurately flip the Y-coordinates of the segmentations.

Usage

st_invert_y(sf, type = c("POINT", "POLYGON"), img_height, scalef)

Arguments

sf	sf an sf class object read from a .geojson file.
type	character(1) "POINT" for cell centroid, or "POLYGON" for cell segmentation mask. Default is "POINT".
img_height	numeric(1) The total length along the Y axis of the image. Obtained by reading in hires or lowres .png under ⁠/spatial⁠ folder with magick::image_read().
scalef	numeric(1) The scaling factor from a ⁠/spatial/scalefactors_json.json⁠ file

Value

an sf object with Y-axis of the points or polygons flipped

Author(s)

Estella YiXing Dong

Examples

geojson_file <- system.file(
    file.path("extdata", "segmented_outputs", "cell_segmentations.geojson"),
    mustWork = TRUE, package = "VisiumIO"
)
geo_data <- sf::st_read(geojson_file, quiet = TRUE)
st_invert_y(
    sf = geo_data, type = "POLYGON", img_height = 3886, scalef = 0.079
)

---

Import 10X Genomics GeoJSON files

Description

TENxGeoJSON is a class to represent and import GeoJSON files from 10X Genomics. It is a composed class of TENxIO::TENxFile.

Usage

TENxGeoJSON(resource)

## S4 method for signature 'TENxGeoJSON,ANY,ANY'
import(con, format, text, ...)

Arguments

resource	character(1) The path to the file
con	The connection from which data is loaded or to which data is saved. If this is a character vector, it is assumed to be a file name and a corresponding file connection is created and then closed after exporting the object. If it is a BiocFile derivative, the data is loaded from or saved to the underlying resource. If missing, the function will return the output as a character vector, rather than writing to a connection.
format	The format of the output. If missing and con is a file name, the format is derived from the file extension. This argument is unnecessary when con is a derivative of BiocFile.
text	If con is missing, this can be a character vector directly providing the string data to import.
...	Additional inputs to the low level class generator functions

Details

Typically, the user will not create an object of this class directly but rather use the TENxVisium() constructor function to create an object of this class in the background.

Value

TENxGeoJSON(): An object of class TENxGeoJSON

import-method: An sf and data.frame with the GeoJSON data

See Also

https://www.10xgenomics.com/support/software/xenium-ranger/3.0/analysis/segmentation-inputs

Examples

segout_folder <- system.file(
    file.path("extdata", "segmented_outputs"),
    package = "VisiumIO"
)

## import cell boundaries
cellsegs <- file.path(segout_folder, "cell_segmentations.geojson")

TENxGeoJSON(cellsegs)

TENxGeoJSON(cellsegs) |>
    import()

## import nucleus boundaries
nucsegs <- file.path(segout_folder, "nucleus_segmentations.geojson")

TENxGeoJSON(nucsegs) |>
    import()

---

Represent and import Parquet data from 10X Genomics

Description

TENxParquet is a virtual class to represent and import Parquet files from 10X Genomics. It is a composed class of TENxIO::TENxFile.

TENxSpatialParquet is a class to represent and import spatial Parquet files from 10X Genomics. It is a composed class of TENxIO::TENxFile.

Usage

TENxParquet(resource, type = c("spatial", "mapping"))

TENxMappingParquet(resource, colnames = .MAPPING_POS_COLS)

## S4 method for signature 'TENxMappingParquet,ANY,ANY'
import(con, format, text, ...)

Arguments

resource	character(1) The path to the file
type	character(1) A scalar specifying the type of Parquet file to import, either "spatial" or "mapping". If not provided, the type is determined by whether or not there is a "mapping" keyword in the file name.
colnames	character() A vector specifying the column names of the Parquet, defaults to all columns in the dataset.
con	The connection from which data is loaded or to which data is saved. If this is a character vector, it is assumed to be a file name and a corresponding file connection is created and then closed after exporting the object. If it is a BiocFile derivative, the data is loaded from or saved to the underlying resource. If missing, the function will return the output as a character vector, rather than writing to a connection.
format	The format of the output. If missing and con is a file name, the format is derived from the file extension. This argument is unnecessary when con is a derivative of BiocFile.
text	If con is missing, this can be a character vector directly providing the string data to import.
...	Additional inputs to the low level class generator functions

Details

Typically, the user will not create an object of this class directly but rather use the TENxParquet constructor function to create an object of either TENxSpatialParquet or TENxMappingParquet class in the background.

Value

TENxParquet(): An object of class TENxSpatialParquet or TENxMappingParquet

TENxMappingParquet(): An object of class TENxMappingParquet

Examples

sample_dir <- system.file(
    file.path("extdata", "binned_outputs", "square_002um", "spatial"),
    package = "VisiumIO"
)
spatial_dir <- Filter(
    function(x) endsWith(x, "spatial"), list.dirs(sample_dir)
)
parquetres <- file.path(spatial_dir, "tissue_positions.parquet")
TENxParquet(parquetres)
parq_file <- system.file(
    "extdata", "barcode_mappings.parquet",
    package = "VisiumIO", mustWork = TRUE
)
TENxMappingParquet(parq_file)

---

Represent and import spatial CSV data from 10X Genomics

Description

TENxSpatialCSV is a class to represent and import spatial CSV files with specific column names. It is a composed class of TENxIO::TENxFile and contains additional slots for the column names and whether the CSV is a list-type of file.

Usage

TENxSpatialCSV(resource, colnames = .TISSUE_POS_COLS)

## S4 method for signature 'TENxSpatialCSV,ANY,ANY'
import(con, format, text, ...)

Arguments

resource	character(1) The path to the file
colnames	character() A vector specifying the column names of the CSV, defaults to c("barcode", "in_tissue", "array_row", "array_col", "pxl_row_in_fullres", "pxl_col_in_fullres"). Mainly used for the "positions" CSV type of file which does not include column names in the file.
con	The connection from which data is loaded or to which data is saved. If this is a character vector, it is assumed to be a file name and a corresponding file connection is created and then closed after exporting the object. If it is a BiocFile derivative, the data is loaded from or saved to the underlying resource. If missing, the function will return the output as a character vector, rather than writing to a connection.
format	The format of the output. If missing and con is a file name, the format is derived from the file extension. This argument is unnecessary when con is a derivative of BiocFile.
text	If con is missing, this can be a character vector directly providing the string data to import.
...	Additional inputs to the low level class generator functions

Details

Typically, the user will not create an object of this class directly but rather use the TENxVisium() constructor function to create an object of this class in the background. The column names are set to the default values of c("barcode", "in_tissue", "array_row", "array_col", "pxl_row_in_fullres", "pxl_col_in_fullres"). The column names can be changed by specifying the colnames argument in the constructor function.

Set the option "VisiumIO.csvreader" to either "data.table" or "readr" to use the data.table::fread or readr::read_csv functions, respectively. These options are useful when the CSV file is relatively large and the user wants to use faster read-in options. Note that the outputs will still be converted to DataFrame when incorporated to the SpatialExperiment or SingleCellExperiment object.

Value

TENxSpatialCSV: An object of class TENxSpatialCSV

import-method: A DataFrame object containing the data from the CSV file

Slots

isList

logical(1) A scalar specifying whether the CSV is a list-type of file

colnames

character() A vector specifying the column names of the CSV

variant

character(1) A scalar specifying the variant of the CSV file "positions", "cell_boundaries", or "other". The variant is determined by the name of the CSV file within the constructor function. Values include "positions", "cell_boundaries", and "other".

compressed

logical(1) A scalar specifying whether the CSV is compressed (mainly with a .gz file extension).

Examples

sample_dir <- system.file(
    file.path("extdata", "10xVisium", "section1"),
    package = "VisiumIO"
)
spatial_dir <- Filter(
  function(x) endsWith(x, "spatial"), list.dirs(sample_dir)
)
csvresource <- file.path(spatial_dir, "tissue_positions_list.csv")
TENxSpatialCSV(csvresource)
head(import(TENxSpatialCSV(csvresource)), 4)

import(TENxSpatialCSV(csvresource)) |>
    attr("metadata") |>
    lapply(names)

---

A class to represent and import spatial Visium data

Description

This class is a composed class of TENxFileList, which can contain a list of TENxFile objects, and a TENxSpatialList object. It is meant to handle spatial Visium data from 10X Genomics.

Usage

TENxSpatialList(
  resources,
  sample_id = "sample01",
  images = c("lowres", "hires", "detected", "aligned", "aligned_fiducials", "cytassist"),
  jsonFile = .SCALE_JSON_FILE,
  tissuePattern = "tissue_positions.*",
  bin_size = character(0L),
  loadImage = FALSE,
  ...
)

## S4 method for signature 'TENxSpatialList,ANY,ANY'
import(con, format, text, ...)

Arguments

resources	A TENxFileList object or a file path to the tarball containing the matrix / assay data resources.
sample_id	character(1) A single string specifying the sample ID.
images	character() A vector specifying the images to be imported; can be one or multiple of "lowres", "hires", "detected", "aligned".
jsonFile	character(1) A single string specifying the name of the JSON file containing the scale factors.
tissuePattern	character(1) A single string specifying the pattern to match the tissue positions file.
bin_size	character(1) The bin size of the images to import. The default is 008. It corresponds to the directory name square_000um where 000 is the bin value.
loadImage	logical(1) A single logical value indicating whether to load the image data into the resulting SpatialExperiment object. This argument requires the magick package.
...	Parameters to pass to the format-specific method.
con	The connection from which data is loaded or to which data is saved. If this is a character vector, it is assumed to be a file name and a corresponding file connection is created and then closed after exporting the object. If it is a BiocFile derivative, the data is loaded from or saved to the underlying resource. If missing, the function will return the output as a character vector, rather than writing to a connection.
format	The format of the output. If missing and con is a file name, the format is derived from the file extension. This argument is unnecessary when con is a derivative of BiocFile.
text	If con is missing, this can be a character vector directly providing the string data to import.

Details

Typically, the user will not create an object of this class directly but rather use the TENxVisium() constructor function to create an object of this class.

Value

A SpatialExperiment object

Methods (by generic)

• import(con = TENxSpatialList, format = ANY, text = ANY): Import a TENxSpatialList object

Slots

images

character() The image name(s) to use with grep and include in the list of files. Can be one of "lowres", "hires", "lowres", "hires", "detected", "aligned", "aligned_fiducials", or "cytassist".

scaleJSON

character(1) The file name of the scale factors JSON file, defaults to 'scalefactors_json.json'.

tissuePos

character(1) The file name of the tissue positions file; typically a .parquet or .csv file.

sampleId

character(1) A scalar specifying the sample identifier.

binSize

The bin size of the images to import. The default slot value is character(). It typically corresponds to the directory name square_000um where 000 is the bin value.

loadImage

logical(1) Whether to load the images into memory as SpatialImage objects. If FALSE, the images are stored as file paths and loaded as StoredSpatialImage objects when the TENxSpatialList object is imported. The default is FALSE to avoid loading large images into memory. This functionality requires the magick package.

Examples

spatial_dir <- system.file(
    file.path("extdata", "10xVisium", "section1", "outs", "spatial"),
    package = "VisiumIO"
)

TENxSpatialList(resources = spatial_dir, images = "lowres")

TENxSpatialList(resources = spatial_dir, images = "lowres") |>
    metadata() |> lapply(names)

---

Represent and import spatial Parquet data from 10X Genomics

Description

TENxSpatialParquet is a class to represent and import spatial Parquet files with specific column names. It is a composed class of TENxIO::TENxFile and contains additional slots for the column names and whether the Parquet is a list-type of file.

Usage

TENxSpatialParquet(resource, colnames)

## S4 method for signature 'TENxSpatialParquet,ANY,ANY'
import(con, format, text, ...)

Arguments

resource	character(1) The path to the file
colnames	character() A vector specifying the column names of the Parquet, defaults to all columns in the dataset.
con	The connection from which data is loaded or to which data is saved. If this is a character vector, it is assumed to be a file name and a corresponding file connection is created and then closed after exporting the object. If it is a BiocFile derivative, the data is loaded from or saved to the underlying resource. If missing, the function will return the output as a character vector, rather than writing to a connection.
format	The format of the output. If missing and con is a file name, the format is derived from the file extension. This argument is unnecessary when con is a derivative of BiocFile.
text	If con is missing, this can be a character vector directly providing the string data to import.
...	Additional inputs to the low level class generator functions

Details

Typically, the user will not create an object of this class directly but rather use the TENxVisium() constructor function to create an object of this class in the background. The column names are set to the default values of c("barcode", "in_tissue", "array_row", "array_col", "pxl_row_in_fullres", "pxl_col_in_fullres"). The column names can be changed by specifying the colnames argument in the constructor function.

Value

TENxSpatialParquet(): An object of class TENxSpatialParquet

import-method: A tibble object containing the data from the Parquet file

Examples

sample_dir <- system.file(
    file.path("extdata", "binned_outputs", "square_002um", "spatial"),
    package = "VisiumIO"
)
spatial_dir <- Filter(
    function(x) endsWith(x, "spatial"), list.dirs(sample_dir)
)
parquetres <- file.path(spatial_dir, "tissue_positions.parquet")
TENxSpatialParquet(parquetres)
TENxSpatialParquet(parquetres) |>
    import()

## metadata in attributes
TENxSpatialParquet(parquetres) |>
    import() |>
    attr("metadata") |>
    lapply(names)

---

A class to represent and import a single Visium Sample

Description

This class is a composed class of TENxFileList which can contain a list of TENxFile objects and a TENxSpatialList object. It is meant to handle a single Visium sample from 10X Genomics.

Usage

TENxVisium(
  resources,
  spatialResource,
  spacerangerOut,
  sample_id = "sample01",
  processing = c("filtered", "raw"),
  format = c("mtx", "h5"),
  images = c("lowres", "hires", "detected", "aligned", "cytassist"),
  jsonFile = .SCALE_JSON_FILE,
  tissuePattern = "tissue_positions.*\\.csv",
  spatialCoordsNames = c("pxl_col_in_fullres", "pxl_row_in_fullres"),
  loadImage = FALSE,
  ...
)

## S4 method for signature 'TENxVisium,ANY,ANY'
import(con, format, text, ...)

Arguments

resources	A TENxFileList object or a file path to the tarball containing the matrix / assay data resources.
spatialResource	A TENxSpatialList object or a file path to the tarball containing the spatial data.
spacerangerOut	character(1) A single string specifying the path to the directory where the output of ⁠spaceranger count⁠ is located; typically (but not necessarily), this is the outs directory. The directory must contain the ⁠(processing)_feature_bc_matrix⁠ and spatial sub directories.
sample_id	character(1) A single string specifying the sample ID.
processing	character(1) A single string indicating the processing folder available e.g., "filtered_feature_barcode_matrix" in the spacerangerOut folder. It can be either "filtered" or "raw" (default "filtered"). Only used when spacerangerOut is specified.
format	The format of the output. If missing and con is a file name, the format is derived from the file extension. This argument is unnecessary when con is a derivative of BiocFile.
images	character() A vector specifying the images to be imported; can be one or multiple of "lowres", "hires", "detected", "aligned".
jsonFile	character(1) A single string specifying the name of the JSON file containing the scale factors.
tissuePattern	character(1) A single string specifying the pattern to match the tissue positions file.
spatialCoordsNames	character() A vector of strings specifying the names of the columns in the spatial data containing the spatial coordinates.
loadImage	logical(1) A single logical value indicating whether to load the image data into the resulting SpatialExperiment object. This argument requires the magick package.
...	In the constructor, additional arguments passed to TENxFileList; otherwise, not used.
con	The connection from which data is loaded or to which data is saved. If this is a character vector, it is assumed to be a file name and a corresponding file connection is created and then closed after exporting the object. If it is a BiocFile derivative, the data is loaded from or saved to the underlying resource. If missing, the function will return the output as a character vector, rather than writing to a connection.
text	If con is missing, this can be a character vector directly providing the string data to import.

Details

Typically, the user will not create an object of this class directly but rather use TENxVisiumList constructor function for multiple samples. Note that the images, jsonFile, tissuePattern, and spatialCoordsNames arguments are only considered when the spacerangerOut argument or both the resources and spatialResource arguments are paths to files.

Value

A SpatialExperiment object

Functions

• import(con = TENxVisium, format = ANY, text = ANY): Import Visium data

Slots

resources

A TENxFileList or TENxH5 object containing the Visium data.

spatialList

A TENxSpatialList object containing the spatial

coordNames

character() A vector specifying the names of the columns in the spatial data containing the spatial coordinates.

sampleId

character(1) A scalar specifying the sample identifier.

loadImage

logical(1) Whether to load the images into memory as SpatialImage objects. If FALSE, the images are stored as file paths and loaded as StoredSpatialImage objects when the TENxSpatialList object is imported. The default is FALSE to avoid loading large images into memory. This functionality requires the magick package.

See Also

https://support.10xgenomics.com/spatial-gene-expression/software/pipelines/latest/output/overview

Examples

outs_dir <- system.file(
    file.path("extdata", "10xVisium", "section1", "outs"),
    package = "VisiumIO"
)

## using spacerangerOut folder
tv <- TENxVisium(
    spacerangerOut = outs_dir, processing = "raw", images = "lowres"
)

import(tv)

## with TENxFileList spacerangerOut input
tvfl <- TENxVisium(
    spacerangerOut = TENxFileList(outs_dir),
    format = "mtx",
    processing = "raw",
    images = "lowres"
)

import(tvfl)

## check metadata of the object
import(tvfl) |>
    metadata() |>
    lapply(names)

## importing h5 format
tvfl <- TENxVisium(
    spacerangerOut = outs_dir,
    format = "h5",
    processing = "raw",
    images = "lowres"
)

import(tvfl)

rffolder <- file.path(outs_dir, "raw_feature_bc_matrix")
## using resources and spatialResource inputs
tvfl <- TENxVisium(
    resources = rffolder,
    spatialResource = file.path(dirname(rffolder), "spatial"),
    format = "mtx",
    processing = "raw",
    images = "lowres"
)

import(tvfl)

---

A class to represent and import multiple Visium HD samples

Description

This class contains a SimpleList of TENxVisiumHD objects each corresponding to one sample. The provided spacerangerOut folder should contain a binned_outputs folder where multiple bin_size subfolders are present, e.g., square_002um. Note that the sf package is required to import cell segmentation and nucleus segmentation data. If the sf package is not installed, the cell segmentation data will not be imported and an error is issued.

Usage

TENxVisiumHD(
  resources,
  spatialResource,
  spacerangerOut,
  segmented_outputs,
  sample_id = "sample01",
  processing = c("filtered", "raw"),
  format = c("mtx", "h5"),
  images = c("lowres", "hires", "detected", "aligned_fiducials"),
  bin_size = c("008", "016", "002"),
  jsonFile = .SCALE_JSON_FILE,
  tissuePattern = "tissue_positions\\.parquet",
  spatialCoordsNames = c("pxl_col_in_fullres", "pxl_row_in_fullres"),
  mappingPattern = "barcode_mappings\\.parquet",
  boundary = c("cell_segmentations", "nucleus_segmentations", "both"),
  loadImage = FALSE,
  ...
)

## S4 method for signature 'TENxVisiumHD,ANY,ANY'
import(con, format, text, ...)

Arguments

resources	A TENxFileList object or a file path to the tarball containing the matrix / assay data resources.
spatialResource	A TENxSpatialList object or a file path to the tarball containing the spatial data.
spacerangerOut	character(1) A single string specifying the path to the directory where the output of ⁠spaceranger count⁠ is located; typically (but not necessarily), this is the outs directory. The directory must contain the ⁠(processing)_feature_bc_matrix⁠ and spatial sub directories.
segmented_outputs	character(1) The path to the segmented_outputs directory
sample_id	character(1) A single string specifying the sample ID.
processing	character(1) A single string indicating the processing folder available e.g., "filtered_feature_barcode_matrix" in the spacerangerOut folder. It can be either "filtered" or "raw" (default "filtered"). Only used when spacerangerOut is specified.
format	The format of the output. If missing and con is a file name, the format is derived from the file extension. This argument is unnecessary when con is a derivative of BiocFile.
images	character() A vector specifying the images to be imported; can be one or multiple of "lowres", "hires", "detected", "aligned".
bin_size	character(1) The bin size of the images to import. The default is 008. It corresponds to the directory name square_000um where 000 is the bin value.
jsonFile	character(1) A single string specifying the name of the JSON file containing the scale factors.
tissuePattern	character(1) A single string specifying the pattern to match the tissue positions file.
spatialCoordsNames	character() A vector of strings specifying the names of the columns in the spatial data containing the spatial coordinates.
mappingPattern	character(1) The pattern used in list.files that identifies the mapping file. The default is "barcode_mappings\\.parquet".
boundary	character(1) The type of segmentation boundary to use. The options are "cell_segmentations" (default), "nucleus_segmentations", or "⁠both"⁠. When "both" is specified, "cell_segmentations" are added to the spatialCoords and the nucleus_segmentations centroids (labeled x.nuc and y.nuc) are added to the colData of the returned object.
loadImage	logical(1) A single logical value indicating whether to load the image data into the resulting SpatialExperiment object. This argument requires the magick package.
...	In the constructor, additional arguments passed to TENxFileList; otherwise, not used.
con	The connection from which data is loaded or to which data is saved. If this is a character vector, it is assumed to be a file name and a corresponding file connection is created and then closed after exporting the object. If it is a BiocFile derivative, the data is loaded from or saved to the underlying resource. If missing, the function will return the output as a character vector, rather than writing to a connection.
text	If con is missing, this can be a character vector directly providing the string data to import.

Details

Typically, the user will provide a path to a directory containing the output of the ⁠spaceranger count⁠ command. The ⁠spaceranger count⁠ command outputs a folder containing the "raw" or "filtered" ⁠()_feature_bc_matrix⁠.

Note that nucleus_segmentations.geojson file must be in the same folder as the cell_segmentations.geojson file for the nucleus centroids to be imported correctly when selecting the "both" for the boundary argument.

Value

A SpatialExperiment object

Functions

• import(con = TENxVisiumHD, format = ANY, text = ANY): Import Visium HD data from multiple bin sizes

Author(s)

E. Y. Dong, M. Ramos

Examples

vdir <- system.file(
    "extdata", package = "VisiumIO", mustWork = TRUE
)

## with spacerangerOut folder
TENxVisiumHD(spacerangerOut = vdir, bin_size = "002", images = "lowres")

TENxVisiumHD(spacerangerOut = vdir, bin_size = "002", images = "lowres") |>
    import()

## indicate h5 format
TENxVisiumHD(
    spacerangerOut = vdir, bin_size = "002",
    images = "lowres", format = "h5"
)

TENxVisiumHD(
    spacerangerOut = vdir, bin_size = "002",
    images = "lowres", format = "h5"
) |>
    import()

## use resources and spatialResource arguments as file paths
TENxVisiumHD(
    resources = file.path(
        vdir, "binned_outputs", "square_002um",
        "filtered_feature_bc_matrix.h5"
    ),
    spatialResource = file.path(
        vdir, "binned_outputs", "square_002um",
        "spatial"
    ),
    bin_size = "002", processing = "filtered",
    images = "lowres", format = "h5"
) |>
    import()

## provide the spatialResource argument as a TENxFileList
TENxVisiumHD(
    resources = file.path(
        vdir, "binned_outputs", "square_002um",
        "filtered_feature_bc_matrix.h5"
    ),
    spatialResource = TENxFileList(
        file.path(
            vdir, "binned_outputs", "square_002um",
            "spatial"
        )
    ),
    bin_size = "002", images = "lowres", format = "h5"
) |>
    import()

## with segmented_outputs folder
seg_outs <- system.file(
    "extdata", "segmented_outputs", package = "VisiumIO", mustWork = TRUE
)
TENxVisiumHD(
    segmented_outputs = seg_outs,
    format = "h5",
    images = "lowres"
) |>
    import()

---

A class to represent and import multiple Visium samples

Description

This class contains a SimpleList of TENxVisium objects each corresponding to one sample.

Usage

TENxVisiumList(
  sampleFolders,
  sample_ids,
  processing = c("filtered", "raw"),
  images = c("lowres", "hires", "detected", "aligned"),
  format = c("mtx", "h5"),
  jsonFile = .SCALE_JSON_FILE,
  tissuePattern = "tissue_positions.*\\.csv",
  spatialCoordsNames = c("pxl_col_in_fullres", "pxl_row_in_fullres"),
  ...
)

## S4 method for signature 'TENxVisiumList,ANY,ANY'
import(con, format, text, ...)

Arguments

sampleFolders	character() A vector of strings specifying the directories containing the output of the ⁠spaceranger count⁠ command.
sample_ids	character() A vector of strings specifying the sample IDs. If not provided, the sample IDs will be the names of the sampleFolders. Therefore, the sample_ids must be the same length as sampleFolders.
processing	character(1) A single string indicating the processing folder available e.g., "filtered_feature_barcode_matrix" in the spacerangerOut folder. It can be either "filtered" or "raw" (default "filtered"). Only used when spacerangerOut is specified.
images	character() A vector specifying the images to be imported; can be one or multiple of "lowres", "hires", "detected", "aligned".
format	The format of the output. If missing and con is a file name, the format is derived from the file extension. This argument is unnecessary when con is a derivative of BiocFile.
jsonFile	character(1) A single string specifying the name of the JSON file containing the scale factors.
tissuePattern	character(1) A single string specifying the pattern to match the tissue positions file.
spatialCoordsNames	character() A vector of strings specifying the names of the columns in the spatial data containing the spatial coordinates.
...	In the constructor, additional arguments passed to TENxFileList; otherwise, not used.
con	The connection from which data is loaded or to which data is saved. If this is a character vector, it is assumed to be a file name and a corresponding file connection is created and then closed after exporting the object. If it is a BiocFile derivative, the data is loaded from or saved to the underlying resource. If missing, the function will return the output as a character vector, rather than writing to a connection.
text	If con is missing, this can be a character vector directly providing the string data to import.

Details

Typically, the user will provide a path to a directory containing the output of the ⁠spaceranger count⁠ command. The ⁠spaceranger count⁠ command outputs a folder containing the "raw" or "filtered" ⁠()_feature_bc_matrix⁠.

Value

A SpatialExperiment object

Functions

• import(con = TENxVisiumList, format = ANY, text = ANY): Import multiple Visium samples

See Also

https://support.10xgenomics.com/spatial-gene-expression/software/pipelines/latest/output/overview

Examples

sample_dirs <- list.dirs(
    system.file(
        file.path("extdata", "10xVisium"),
        package = "VisiumIO"
    ),
    recursive = FALSE, full.names = TRUE
)

tvl <- TENxVisiumList(
    sampleFolders = sample_dirs,
    sample_ids = c("sample01", "sample02"),
    processing = "raw",
    images = "lowres",
    format = "mtx"
)

import(tvl)

---