1. spatialDE
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Add documentation for the S4 methods

Milan Malfait authored on 09/03/2021 10:36:11
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R/spatialDE.R
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-
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+#' Find spatially variable genes with **SpatialDE**
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+#'
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+#' Identify genes that significantly depend on spatial coordinates with the
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+#' [**SpatialDE**](https://github.com/Teichlab/SpatialDE) Python package.
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+#'
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+#' @param x A numeric `matrix` of counts where genes are rows and cells are columns.
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+#'
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+#'    Alternatively, a \linkS4class{SpatialExperiment} object.
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+#'
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+#' @param ... For the generic, arguments to pass to specific methods.
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+#' @param coordinates A `data.frame` with sample coordinates. Each row is a
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+#'   sample, the columns with coordinates should be named 'x' and 'y'.
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+#'
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+#'   For the *SpatialExperiment* method, coordinates are taken from
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+#'   `spatialCoords(x)`.
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+#'
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+#' @param assay_type A `character` string specifying the assay from `x` to use
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+#'   as input. Defaults to `"counts"`.
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+#' @param verbose A `logical` controlling the display of a progress bar from the
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+#'   Python package.
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+#'
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+#' @return A `data.frame` with DE results where each row is a gene and columns
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+#'   contain relevant statistics.
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+#'
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+#'   The most important columns are:
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+#'
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+#'   * `g`: the name of the gene
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+#'   * `pval`: the p-value for spatial differential expression
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+#'   * `qval`: the q-value, indicating significance after correcting for
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+#'   multiple testing
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+#'   * `l`: A parameter indicating the distance scale a gene changes expression
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+#'   over
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+#'
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+#' @examples
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+#' ## Mock up a SpatialExperiment object wit 100 cells, 200 genes
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+#' set.seed(42)
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+#' spe <- mockSVG(size = 10, tot_genes = 200, de_genes = 20, return_SPE = TRUE)
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+#'
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+#' ## Run spatialDE
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+#' de_results <- spatialDE(spe)
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+#' head(de_results)
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+#'
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+#' @seealso
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+#' The individual steps performed by this function: [stabilize()],
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+#' [regress_out()] and [run()].
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+#'
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+#' For further analysis of the DE results:
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+#' [model_search()] and [spatial_patterns()].
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+#'
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+#' @references
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+#' Svensson, V., Teichmann, S. & Stegle, O. SpatialDE: identification of
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+#' spatially variable genes. Nat Methods 15, 343–346 (2018).
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+#' \url{https://doi.org/10.1038/nmeth.4636}
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+#'
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+#' [**SpatialDE 1.1.3**](https://pypi.org/project/SpatialDE/1.1.3/): the version
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+#' of the Python package used under the hood.
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+#'
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+#' @author Davide Corso, Milan Malfait
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+#' @name spatialDE
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+NULL
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 ## Run spatialDE pipeline on any matrix-like object
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 #' @importFrom Matrix colSums
man/spatialDE.Rd
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+% Generated by roxygen2: do not edit by hand
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+% Please edit documentation in R/spatialDE.R
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+\name{spatialDE}
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+\alias{spatialDE}
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+\alias{spatialDE,matrix-method}
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+\alias{spatialDE,SpatialExperiment-method}
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+\title{Find spatially variable genes with \strong{SpatialDE}}
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+\usage{
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+spatialDE(x, ...)
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+
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+\S4method{spatialDE}{matrix}(x, coordinates, verbose = FALSE)
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+
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+\S4method{spatialDE}{SpatialExperiment}(x, assay_type = "counts", verbose = FALSE)
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+}
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+\arguments{
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+\item{x}{A numeric \code{matrix} of counts where genes are rows and cells are columns.
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+
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+Alternatively, a \linkS4class{SpatialExperiment} object.}
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+
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+\item{...}{For the generic, arguments to pass to specific methods.}
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+
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+\item{coordinates}{A \code{data.frame} with sample coordinates. Each row is a
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+sample, the columns with coordinates should be named 'x' and 'y'.
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+
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+For the \emph{SpatialExperiment} method, coordinates are taken from
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+\code{spatialCoords(x)}.}
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+
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+\item{verbose}{A \code{logical} controlling the display of a progress bar from the
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+Python package.}
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+
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+\item{assay_type}{A \code{character} string specifying the assay from \code{x} to use
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+as input. Defaults to \code{"counts"}.}
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+}
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+\value{
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+A \code{data.frame} with DE results where each row is a gene and columns
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+contain relevant statistics.
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+
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+The most important columns are:
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+\itemize{
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+\item \code{g}: the name of the gene
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+\item \code{pval}: the p-value for spatial differential expression
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+\item \code{qval}: the q-value, indicating significance after correcting for
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+multiple testing
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+\item \code{l}: A parameter indicating the distance scale a gene changes expression
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+over
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+}
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+}
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+\description{
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+Identify genes that significantly depend on spatial coordinates with the
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+\href{https://github.com/Teichlab/SpatialDE}{\strong{SpatialDE}} Python package.
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+}
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+\examples{
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+## Mock up a SpatialExperiment object wit 100 cells, 200 genes
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+set.seed(42)
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+spe <- mockSVG(size = 10, tot_genes = 200, de_genes = 20, return_SPE = TRUE)
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+
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+## Run spatialDE
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+de_results <- spatialDE(spe)
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+head(de_results)
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+
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+}
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+\references{
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+Svensson, V., Teichmann, S. & Stegle, O. SpatialDE: identification of
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+spatially variable genes. Nat Methods 15, 343–346 (2018).
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+\url{https://doi.org/10.1038/nmeth.4636}
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+
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+\href{https://pypi.org/project/SpatialDE/1.1.3/}{\strong{SpatialDE 1.1.3}}: the version
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+of the Python package used under the hood.
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+}
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+\seealso{
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+The individual steps performed by this function: \code{\link[=stabilize]{stabilize()}},
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+\code{\link[=regress_out]{regress_out()}} and \code{\link[=run]{run()}}.
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+
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+For further analysis of the DE results:
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+\code{\link[=model_search]{model_search()}} and \code{\link[=spatial_patterns]{spatial_patterns()}}.
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+}
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+\author{
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+Davide Corso, Milan Malfait
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+}