@@ -4,17 +4,25 @@

 #' Expression Histology, using the

 #' [**SpatialDE**](https://github.com/Teichlab/SpatialDE) Python package.

 #'

-#' @param x \linkS4class{SpatialExperiment} object.

+#' @param x A numeric `matrix` of counts where genes are rows and cells are columns.

+#'

+#'    Alternatively, a \linkS4class{SpatialExperiment} object.

 #'

 #' @param ... For the generic, arguments to pass to specific methods.

-#' @param assay_type A `character` string specifying the assay from `x` to use

-#'   as input. Defaults to `"counts"`.

 #' @param de_results `data.frame` resulting from [run()] or [spatialDE()].

+#' @param coordinates A `data.frame` with sample coordinates. Each row is a

+#'   sample, the columns with coordinates should be named 'x' and 'y'.

+#'

+#'   For the *SpatialExperiment* method, coordinates are taken from

+#'   `spatialCoords(x)`.

+#'

 #' @param qval_thresh `numeric` scalar, specifying the q-value significance

 #'   threshold to filter `de_results`. Only rows in `de_results` with

 #'   `qval < qval_thresh` will be kept. To disable, set `qval_thresh = NULL`.

 #' @param n_patterns `integer` The number of spatial patterns

 #' @param length `numeric` The characteristic length scale of the clusters

+#' @param assay_type A `character` string specifying the assay from `x` to use

+#'   as input. Defaults to `"counts"`.

 #' @param verbose A `logical` controlling the display of a progress bar from the

 #'   Python package.

 #'

@@ -59,36 +67,51 @@

 NULL

 #' @importFrom Matrix colSums

-.spatialPatterns <- function(counts_spe, coordinates_spe, de_results,

-                             n_patterns, length, verbose = FALSE) {

-  sample_info <- data.frame(coordinates_spe, total_counts = colSums(counts_spe))

+#' @importFrom checkmate assert_data_frame assert_number assert_int assert_flag

+.spatialPatterns <- function(x, de_results, coordinates,

+                             qval_thresh = 0.05, n_patterns, length,

+                             verbose = FALSE) {

+    assert_data_frame(de_results, all.missing = FALSE)

+    assert_number(qval_thresh, null.ok = TRUE)

+    assert_int(n_patterns, coerce = TRUE)

+    assert_number(length)

+    assert_flag(verbose)

+

+    ## Filter de_results

+    if (!is.null(qval_thresh)) {

+        de_results <- .filter_de_results(

+            de_results = de_results, qval_thresh = qval_thresh

+        )

+    }

+

+    sample_info <- data.frame(coordinates, total_counts = colSums(x))

-  out <- basilisk::basiliskRun(

-      env = spatialDE_env,

-      fun = .run_spatial_patterns,

-      counts_spe = counts_spe,

-      sample_info = sample_info,

-      de_results = de_results,

-      n_patterns = n_patterns,

-      length = length,

-      verbose = verbose

-  )

-  out

+    out <- basilisk::basiliskRun(

+        env = spatialDE_env,

+        fun = .run_spatial_patterns,

+        x = x,

+        sample_info = sample_info,

+        de_results = de_results,

+        n_patterns = n_patterns,

+        length = length,

+        verbose = verbose

+    )

+    out

 }

-.run_spatial_patterns <- function(counts_spe, sample_info,

-                                  de_results, n_patterns, length,

+.run_spatial_patterns <- function(x, sample_info, de_results,

+                                  n_patterns, length,

                                   verbose = FALSE) {

-  ## Normalization

-  stabilized <- .naiveDE_stabilize(counts = counts_spe)

-  regressed <- .naiveDE_regress_out(counts = stabilized, sample_info)

+    ## Normalization

+    stabilized <- .naiveDE_stabilize(counts = x)

+    regressed <- .naiveDE_regress_out(counts = stabilized, sample_info)

-  coordinates <- sample_info[, c("x", "y")]

-  .spatialDE_spatial_patterns(

-      x = regressed, coordinates = coordinates,

-      de_results = de_results, n_patterns = n_patterns,

-      length = length, verbose = verbose

-  )

+    coordinates <- sample_info[, c("x", "y")]

+    .spatialDE_spatial_patterns(

+        x = regressed, coordinates = coordinates,

+        de_results = de_results, n_patterns = n_patterns,

+        length = length, verbose = verbose

+    )

 }

 #' @import methods

@@ -99,36 +122,27 @@ setGeneric("spatialPatterns",

     signature = "x"

 )

+#' @export

+#' @rdname spatialPatterns

+setMethod("spatialPatterns", "matrix", .spatialPatterns)

+

 #' @export

 #' @rdname spatialPatterns

 #' @importFrom SummarizedExperiment assay

 #' @importFrom SpatialExperiment spatialCoords spatialCoordsNames<-

-#' @importFrom checkmate assert_data_frame assert_number assert_int assert_flag

 setMethod("spatialPatterns", "SpatialExperiment",

-  function(x, de_results, assay_type = "counts", qval_thresh = 0.05,

-           n_patterns, length, verbose = FALSE) {

-    assert_data_frame(de_results, all.missing = FALSE)

-    assert_number(qval_thresh, null.ok = TRUE)

-    assert_int(n_patterns, coerce = TRUE)

-    assert_number(length)

-    assert_flag(verbose)

+    function(x, de_results, qval_thresh = 0.05,

+             n_patterns, length,

+             assay_type = "counts", verbose = FALSE) {

-    ## Rename spatialCoords columns to "x", "y"

-    spatialCoordsNames(x) <- c("x", "y")

-    coordinates_spe <- as.data.frame(spatialCoords(x))

-    counts_spe <- assay(x, assay_type)

+        ## Rename spatialCoords columns to "x", "y"

+        spatialCoordsNames(x) <- c("x", "y")

+        coordinates <- as.data.frame(spatialCoords(x))

-    ## Filter de_results

-    if (!is.null(qval_thresh)) {

-      de_results <- .filter_de_results(

-        de_results = de_results, qval_thresh = qval_thresh

-      )

+        .spatialPatterns(

+            x = assay(x, assay_type), de_results = de_results,

+            coordinates = coordinates, qval_thresh = qval_thresh,

+            n_patterns = n_patterns, length = length, verbose = verbose

+        )

     }

-

-    .spatialPatterns(

-        counts_spe = counts_spe, coordinates_spe = coordinates_spe,

-        de_results = de_results, n_patterns = n_patterns,

-        length = length, verbose = FALSE

-    )

-  }

 )

@@ -3,15 +3,23 @@

 #' Compare model fits with different models, using the

 #' [**SpatialDE**](https://github.com/Teichlab/SpatialDE) Python package.

 #'

-#' @param x \linkS4class{SpatialExperiment} object.

+#' @param x A numeric `matrix` of counts where genes are rows and cells are columns.

+#'

+#'    Alternatively, a \linkS4class{SpatialExperiment} object.

 #'

 #' @param ... For the generic, arguments to pass to specific methods.

-#' @param assay_type A `character` string specifying the assay from `x` to use

-#'   as input. Defaults to `"counts"`.

 #' @param de_results `data.frame` resulting from [run()] or [spatialDE()].

+#' @param coordinates A `data.frame` with sample coordinates. Each row is a

+#'   sample, the columns with coordinates should be named 'x' and 'y'.

+#'

+#'   For the *SpatialExperiment* method, coordinates are taken from

+#'   `spatialCoords(x)`.

+#'

 #' @param qval_thresh `numeric` scalar, specifying the q-value significance

 #'   threshold to filter `de_results`. Only rows in `de_results` with

 #'   `qval < qval_thresh` will be kept. To disable, set `qval_thresh = NULL`.

+#' @param assay_type A `character` string specifying the assay from `x` to use

+#'   as input. Defaults to `"counts"`.

 #' @param verbose A `logical` controlling the display of a progress bar from the

 #'   Python package.

 #'

@@ -25,12 +33,11 @@

 #' ## Run spatialDE with S4 integration

 #' de_results <- spatialDE(spe)

 #'

-#' ## Run model search with S4 integration

+#' ## Run model search

 #' model_search <- modelSearch(spe, de_results = de_results,

 #'     qval_thresh = NULL, verbose = FALSE

 #' )

 #'

-#'

 #' @seealso

 #' The individual steps performed by this function: [stabilize()],

 #' [regress_out()] and [model_search()].

@@ -48,32 +55,43 @@

 NULL

 #' @importFrom Matrix colSums

-.modelSearch <- function(counts_spe, coordinates_spe, de_results,

-                         verbose = FALSE) {

-  sample_info <- data.frame(coordinates_spe, total_counts = colSums(counts_spe))

+#' @importFrom checkmate assert_data_frame assert_number assert_flag

+.modelSearch <- function(x, de_results, coordinates,

+                         qval_thresh = 0.05, verbose = FALSE) {

+    assert_data_frame(de_results, all.missing = FALSE)

+    assert_number(qval_thresh, null.ok = TRUE)

+    assert_flag(verbose)

+

+    ## Filter de_results

+    if (!is.null(qval_thresh)) {

+        de_results <- .filter_de_results(

+            de_results = de_results, qval_thresh = qval_thresh

+        )

+    }

+

+    sample_info <- data.frame(coordinates, total_counts = colSums(x))

-  out <- basilisk::basiliskRun(

-      env = spatialDE_env,

-      fun = .run_model_search,

-      counts_spe = counts_spe,

-      sample_info = sample_info,

-      de_results = de_results,

-      verbose = verbose

-  )

-  out

+    out <- basilisk::basiliskRun(

+        env = spatialDE_env,

+        fun = .run_model_search,

+        x = x,

+        sample_info = sample_info,

+        de_results = de_results,

+        verbose = verbose

+    )

+    out

 }

-.run_model_search <- function(counts_spe, sample_info, de_results,

-                              verbose = FALSE) {

-  ## Normalization

-  stabilized <- .naiveDE_stabilize(counts = counts_spe)

-  regressed <- .naiveDE_regress_out(counts = stabilized, sample_info)

+.run_model_search <- function(x, sample_info, de_results, verbose = FALSE) {

+    ## Normalization

+    stabilized <- .naiveDE_stabilize(counts = x)

+    regressed <- .naiveDE_regress_out(counts = stabilized, sample_info)

-  coordinates <- sample_info[, c("x", "y")]

-  .spatialDE_model_search(

-      x = regressed, coordinates = coordinates,

-      de_results = de_results, verbose = verbose

-  )

+    coordinates <- sample_info[, c("x", "y")]

+    .spatialDE_model_search(

+        x = regressed, coordinates = coordinates,

+        de_results = de_results, verbose = verbose

+    )

 }

 #' @import methods

@@ -84,33 +102,26 @@ setGeneric("modelSearch",

     signature = "x"

 )

+#' @export

+#' @rdname modelSearch

+setMethod("modelSearch", "matrix", .modelSearch)

+

 #' @export

 #' @rdname modelSearch

 #' @importFrom SummarizedExperiment assay

 #' @importFrom SpatialExperiment spatialCoords spatialCoordsNames<-

-#' @importFrom checkmate assert_data_frame assert_number assert_flag

 setMethod("modelSearch", "SpatialExperiment",

-  function(x, de_results, assay_type = "counts", qval_thresh=0.05,

-           verbose = FALSE) {

-    assert_data_frame(de_results, all.missing = FALSE)

-    assert_number(qval_thresh, null.ok = TRUE)

-    assert_flag(verbose)

+    function(x, de_results, assay_type = "counts",

+             qval_thresh = 0.05, verbose = FALSE) {

-    ## Rename spatialCoords columns to "x", "y"

-    spatialCoordsNames(x) <- c("x", "y")

-    coordinates_spe <- as.data.frame(spatialCoords(x))

-    counts_spe <- assay(x, assay_type)

+        ## Rename spatialCoords columns to "x", "y"

+        spatialCoordsNames(x) <- c("x", "y")

+        coordinates <- as.data.frame(spatialCoords(x))

-    ## Filter de_results

-    if (!is.null(qval_thresh)) {

-      de_results <- .filter_de_results(

-        de_results = de_results, qval_thresh = qval_thresh

-      )

+        .modelSearch(

+            x = assay(x, assay_type), de_results = de_results,

+            coordinates = coordinates, qval_thresh = qval_thresh,

+            verbose = verbose

+        )

     }

-

-    .modelSearch(

-        counts_spe = counts_spe, coordinates_spe = coordinates_spe,

-        de_results = de_results, verbose = FALSE

-    )

-  }

 )

@@ -2,11 +2,14 @@

 % Please edit documentation in R/msearch.R

 \name{modelSearch}

 \alias{modelSearch}

+\alias{modelSearch,matrix-method}

 \alias{modelSearch,SpatialExperiment-method}

 \title{Classify Spatially Variable Genes to interpretable fitting classes}

 \usage{

 modelSearch(x, de_results, ...)

+\S4method{modelSearch}{matrix}(x, de_results, coordinates, qval_thresh = 0.05, verbose = FALSE)

+

 \S4method{modelSearch}{SpatialExperiment}(

   x,

   de_results,

@@ -16,14 +19,19 @@ modelSearch(x, de_results, ...)

 )

 }

 \arguments{

-\item{x}{\linkS4class{SpatialExperiment} object.}

+\item{x}{A numeric \code{matrix} of counts where genes are rows and cells are columns.

+

+Alternatively, a \linkS4class{SpatialExperiment} object.}

 \item{de_results}{\code{data.frame} resulting from \code{\link[=run]{run()}} or \code{\link[=spatialDE]{spatialDE()}}.}

 \item{...}{For the generic, arguments to pass to specific methods.}

-\item{assay_type}{A \code{character} string specifying the assay from \code{x} to use

-as input. Defaults to \code{"counts"}.}

+\item{coordinates}{A \code{data.frame} with sample coordinates. Each row is a

+sample, the columns with coordinates should be named 'x' and 'y'.

+

+For the \emph{SpatialExperiment} method, coordinates are taken from

+\code{spatialCoords(x)}.}

 \item{qval_thresh}{\code{numeric} scalar, specifying the q-value significance

 threshold to filter \code{de_results}. Only rows in \code{de_results} with

@@ -31,6 +39,9 @@ threshold to filter \code{de_results}. Only rows in \code{de_results} with

 \item{verbose}{A \code{logical} controlling the display of a progress bar from the

 Python package.}

+

+\item{assay_type}{A \code{character} string specifying the assay from \code{x} to use

+as input. Defaults to \code{"counts"}.}

 }

 \value{

 \code{data.frame} of model_search results.

@@ -47,12 +58,11 @@ spe <- mockSVG(size = 10, tot_genes = 200, de_genes = 20, return_SPE = TRUE)

 ## Run spatialDE with S4 integration

 de_results <- spatialDE(spe)

-## Run model search with S4 integration

+## Run model search

 model_search <- modelSearch(spe, de_results = de_results,

     qval_thresh = NULL, verbose = FALSE

 )

-

 }

 \references{

 Svensson, V., Teichmann, S. & Stegle, O. SpatialDE: identification of

@@ -2,30 +2,46 @@

 % Please edit documentation in R/aeh.R

 \name{spatialPatterns}

 \alias{spatialPatterns}

+\alias{spatialPatterns,matrix-method}

 \alias{spatialPatterns,SpatialExperiment-method}

 \title{Automatic expression histology in \strong{SpatialDE}}

 \usage{

 spatialPatterns(x, de_results, ...)

+\S4method{spatialPatterns}{matrix}(

+  x,

+  de_results,

+  coordinates,

+  qval_thresh = 0.05,

+  n_patterns,

+  length,

+  verbose = FALSE

+)

+

 \S4method{spatialPatterns}{SpatialExperiment}(

   x,

   de_results,

-  assay_type = "counts",

   qval_thresh = 0.05,

   n_patterns,

   length,

+  assay_type = "counts",

   verbose = FALSE

 )

 }

 \arguments{

-\item{x}{\linkS4class{SpatialExperiment} object.}

+\item{x}{A numeric \code{matrix} of counts where genes are rows and cells are columns.

+

+Alternatively, a \linkS4class{SpatialExperiment} object.}

 \item{de_results}{\code{data.frame} resulting from \code{\link[=run]{run()}} or \code{\link[=spatialDE]{spatialDE()}}.}

 \item{...}{For the generic, arguments to pass to specific methods.}

-\item{assay_type}{A \code{character} string specifying the assay from \code{x} to use

-as input. Defaults to \code{"counts"}.}

+\item{coordinates}{A \code{data.frame} with sample coordinates. Each row is a

+sample, the columns with coordinates should be named 'x' and 'y'.

+

+For the \emph{SpatialExperiment} method, coordinates are taken from

+\code{spatialCoords(x)}.}

 \item{qval_thresh}{\code{numeric} scalar, specifying the q-value significance

 threshold to filter \code{de_results}. Only rows in \code{de_results} with

@@ -37,6 +53,9 @@ threshold to filter \code{de_results}. Only rows in \code{de_results} with

 \item{verbose}{A \code{logical} controlling the display of a progress bar from the

 Python package.}

+

+\item{assay_type}{A \code{character} string specifying the assay from \code{x} to use

+as input. Defaults to \code{"counts"}.}

 }

 \value{

 A \code{list} of two \code{data.frame}s (pattern_results, patterns):