Package 'VisiumIO' reference manual

Title:	Import Visium data from the 10X Space Ranger pipeline
Description:	The package allows users to readily import spatial data obtained from either the 10X website or from the Space Ranger pipeline. Supported formats include tar.gz, h5, and mtx files. Multiple files can be imported at once with *List type of functions. The package represents data mainly as SpatialExperiment objects.
Authors:	Marcel Ramos [aut, cre] , Dario Righelli [aut, ctb], Helena Crowell [aut, ctb]
Maintainer:	Marcel Ramos <[email protected]>
License:	Artistic-2.0
Version:	1.3.1
Built:	2024-10-30 16:18:36 UTC
Source:	https://github.com/waldronlab/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"),
  ...
)
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 sample directory of `⁠spaceranger count⁠`. The directory must contain the `⁠(processing)_feature_bc_matrix⁠` and `spatial` sub directories in addition to the `outs` folder.
`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"
    )
}
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"
    )
}

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, ...)
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 = "SpatialExperiment"
)
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)
sample_dir <- system.file(
    file.path("extdata", "10xVisium", "section1"),
    package = "SpatialExperiment"
)
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"),
  jsonFile = .SCALE_JSON_FILE,
  tissuePattern = "tissue_positions.*",
  bin_size = character(0L),
  ...
)

## S4 method for signature 'TENxSpatialList,ANY,ANY'
import(con, format, text, ...)
TENxSpatialList(
  resources,
  sample_id = "sample01",
  images = c("lowres", "hires", "detected", "aligned", "aligned_fiducials"),
  jsonFile = .SCALE_JSON_FILE,
  tissuePattern = "tissue_positions.*",
  bin_size = character(0L),
  ...
)

## 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.
`...`	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 names to use with grep and include in the list of files.
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.

Examples

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

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

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

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

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 = .TISSUE_POS_COLS)

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

## 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 `c("barcode", "in_tissue", "array_row", "array_col", "pxl_row_in_fullres", "pxl_col_in_fullres")`.
`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

Value

TENxSpatialParquet(): An object of class TENxSpatialParquet

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

Slots

colnames: character() A vector specifying the column names of the Parquet

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)
import(TENxSpatialParquet(parquetres))

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

## metadata in attributes
import(TENxSpatialParquet(parquetres)) |>
    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"),
  jsonFile = .SCALE_JSON_FILE,
  tissuePattern = "tissue_positions.*\\.csv",
  spatialCoordsNames = c("pxl_col_in_fullres", "pxl_row_in_fullres"),
  ...
)

## S4 method for signature 'TENxVisium,ANY,ANY'
import(con, format, text, ...)
TENxVisium(
  resources,
  spatialResource,
  spacerangerOut,
  sample_id = "sample01",
  processing = c("filtered", "raw"),
  format = c("mtx", "h5"),
  images = c("lowres", "hires", "detected", "aligned"),
  jsonFile = .SCALE_JSON_FILE,
  tissuePattern = "tissue_positions.*\\.csv",
  spatialCoordsNames = c("pxl_col_in_fullres", "pxl_row_in_fullres"),
  ...
)

## 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 sample directory of `⁠spaceranger count⁠`. The directory must contain the `⁠(processing)_feature_bc_matrix⁠` and `spatial` sub directories in addition to the `outs` folder.
`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.
`...`	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.

Examples


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

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

import(tv)

## with TENxFileList spacerangerOut input
tvfl <- TENxVisium(
    spacerangerOut = TENxFileList(sample_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 = sample_dir,
    format = "h5",
    processing = "raw",
    images = "lowres"
)

import(tvfl)

rffolder <- file.path(sample_dir, "outs", "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)

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

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

import(tv)

## with TENxFileList spacerangerOut input
tvfl <- TENxVisium(
    spacerangerOut = TENxFileList(sample_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 = sample_dir,
    format = "h5",
    processing = "raw",
    images = "lowres"
)

import(tvfl)

rffolder <- file.path(sample_dir, "outs", "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.

Usage

TENxVisiumHD(
  resources,
  spatialResource,
  spacerangerOut,
  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"),
  ...
)

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

## 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 sample directory of `⁠spaceranger count⁠`. The directory must contain the `⁠(processing)_feature_bc_matrix⁠` and `spatial` sub directories in addition to the `outs` folder.
`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.
`...`	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 = TENxVisiumHD, format = ANY, text = ANY): Import Visium HD data from multiple bin sizes

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()

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()

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, ...)
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

Value

A SpatialExperiment object

Functions

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

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)

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)

Package 'VisiumIO'

Help Index

Compare barcodes between raw and filtered data

Description

Usage

Arguments

Value

Examples

Represent and import spatial CSV data from 10X Genomics

Description

Usage

Arguments

Details

Value

Slots

Examples

A class to represent and import spatial Visium data

Description

Usage

Arguments

Details

Value

Methods (by generic)

Slots

Examples

Represent and import spatial Parquet data from 10X Genomics

Description

Usage

Arguments

Details

Value

Slots

Examples

A class to represent and import a single Visium Sample

Description

Usage

Arguments

Details

Value

Functions

Slots

See Also

Examples

A class to represent and import multiple Visium HD samples

Description

Usage

Arguments

Details

Value

Functions

Examples

A class to represent and import multiple Visium samples

Description

Usage

Arguments

Details

Value

Functions

See Also

Examples