diff --git a/DESCRIPTION b/DESCRIPTION index 7c43840c4..25fda37bb 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,5 +1,5 @@ Package: Seurat -Version: 5.1.0.9019 +Version: 5.2.0 Title: Tools for Single Cell Genomics Description: A toolkit for quality control, analysis, and exploration of single cell RNA sequencing data. 'Seurat' aims to enable users to identify and interpret sources of heterogeneity from single cell transcriptomic measurements, and to integrate diverse types of single cell data. See Satija R, Farrell J, Gennert D, et al (2015) , Macosko E, Basu A, Satija R, et al (2015) , Stuart T, Butler A, et al (2019) , and Hao, Hao, et al (2020) for more details. Authors@R: c( @@ -31,7 +31,7 @@ Authors@R: c( License: MIT + file LICENSE URL: https://satijalab.org/seurat, https://github.com/satijalab/seurat BugReports: https://github.com/satijalab/seurat/issues -Additional_repositories: https://satijalab.r-universe.dev, https://bnprks.r-universe.dev, https://cran.r-universe.dev +Additional_repositories: https://satijalab.r-universe.dev, https://bnprks.r-universe.dev Depends: R (>= 4.0.0), methods, diff --git a/NEWS.md b/NEWS.md index abfd8dbd8..b7d6e9359 100644 --- a/NEWS.md +++ b/NEWS.md @@ -1,27 +1,21 @@ -# Unreleased +# Seurat 5.2.0 (2024-12-20) ## Changes - Added `group.by` parameter to `FindAllMarkers`, allowing users to regroup their data using a non-default identity class prior to performing differential expression ([#9550](https://github.com/satijalab/seurat/pull/9550)) -#' performing differential expression (see example); \code{"ident"} to use Idents - Added `image.type` parameter to `Read10X_Image` enabling `VisiumV1` instances to be populated instead of instances of the default `VisiumV2` class ([#9556](https://github.com/satijalab/seurat/pull/9556)) -- Fixed `IntegrateLayers` to respect the `dims.to.integrate` parameter. +- Fixed `IntegrateLayers` to respect the `dims.to.integrate` parameter - Added `stroke.size` parameter to `DimPlot` ([#8180](https://github.com/satijalab/seurat/pull/8180)) - Updated `RunLeiden` to use the `leidenbase` package instead of `leiden`; deprecated the `method` parameter for `RunLeiden` and `FindClusters`; updated `RunLeiden` to reset `random.seed` to 1 if the value is 0 or less ([#6792](https://github.com/satijalab/seurat/pull/6792)) -- Updated `RunUMAP` to support `umap-learn` version >= 0.5.0 ([#9559](https://github.com/satijalab/seurat/pull/9559)) -- Surfaced more fine-grained control over what parts of a Xenium experiment are loaded in `LoadXenium` -- Added ability to load Xenium nucleus segmentation masks -- Updated `LoadXenium` to also read some run metadata (run start time, preservation method, panel used, organism, tissue type, instrument software version and stain kit used) into `misc` slot -- Updated `ReadXenium` to load cell_feature_matrix.h5 when present in favor of the MEX format files -- Added ability to read Xenium `segmentation_method` directly into `meta.data` -- Updated `ReadXenium` to load .parquet files using `arrow` instead of .csv.gz files to support XOA 3.0 +- Updated `RunPCA` to use the `BPCells`-provided SVD solver on `BPCells` matrices; updated `JackStraw` to support `BPCells` matrices ([#8271](https://github.com/satijalab/seurat/pull/8271)) +- Fixed `RunPCA` to avoid converting `BPCells` matrices into dense matrices - significantly reduces the function's memory usage when running on `BPCells` matrices ([#8966](https://github.com/satijalab/seurat/pull/8966)) - Updated `RunSLSI` to support `BPCells` matrices -- Fixed `LoadXenium` to accommodate datasets without "Blank Codeword" or "Unassigned Codeword" matrices +- Updated `RunUMAP` to support `umap-learn` version >= 0.5.0 ([#9559](https://github.com/satijalab/seurat/pull/9559)) +- Updated `LoadXenium` and `ReadXenium` to accommodate the output from `XOA` v3.0; updated `LoadXenium` to provide more fine-grained control over the datatypes parsed in, including nucleus segmentation masks, segmentation methods, and other experimental metadata; updated `ReadXenium` to load cell_feature_matrix.h5 when present in favor of the MEX format files; updated `ReadXenium` to load .parquet files using `arrow` instead of .csv.gz files to support XOA 3.0 ([#8604](https://github.com/satijalab/seurat/pull/8605)) +- Fixed `LoadXenium` to accommodate datasets without "Blank Codeword" or "Unassigned Codeword" matrices([#9135](https://github.com/satijalab/seurat/pull/9135)) - Fixed `ReadXenium` to properly parse multiple molecular outputs at once ([#8265](https://github.com/satijalab/seurat/issues/8265)) -- Fixed `RunPCA` to avoid converting `BPCells` matrices into dense matrices - significantly reduces the function's memory usage when running on `BPCells` matrices - Added `features` parameter to `LeverageScore` and `SketchData` - Updated `SketchData`'s `ncells` parameter to accept integer vector -- Updated `JackStraw` to support `BPCells` matrices -- Updated `RunPCA` to use the `BPCells`-provided SVD solver on `BPCells` matrices + # Seurat 5.1.0 (2024-05-08) diff --git a/R/clustering.R b/R/clustering.R index 6af115589..8ecddefd4 100644 --- a/R/clustering.R +++ b/R/clustering.R @@ -508,7 +508,7 @@ FindClusters.Seurat <- function( #' distance matrix; note, for objects of class \code{dist}, this parameter will #' be set automatically #' @param k.param Defines k for the k-nearest neighbor algorithm -#' @param return.neighbor Return result as \code{\link{Neighbor}} object. Not +#' @param return.neighbor Return result as \code{\link[SeuratObject]{Neighbor}} object. Not #' used with distance matrix input. #' @param compute.SNN also compute the shared nearest neighbor graph #' @param prune.SNN Sets the cutoff for acceptable Jaccard index when diff --git a/R/generics.R b/R/generics.R index 2e64f7ce8..4ef6f41c9 100644 --- a/R/generics.R +++ b/R/generics.R @@ -156,13 +156,13 @@ FindMarkers <- function(object, ...) { #' @param object An object #' @param ... Arguments passed to other methods #' -#' @return This function can either return a \code{\link{Neighbor}} object -#' with the KNN information or a list of \code{\link{Graph}} objects with +#' @return This function can either return a \code{\link[SeuratObject]{Neighbor}} object +#' with the KNN information or a list of \code{\link[SeuratObject]{Graph}} objects with #' the KNN and SNN depending on the settings of \code{return.neighbor} and -#' \code{compute.SNN}. When running on a \code{\link{Seurat}} object, this -#' returns the \code{\link{Seurat}} object with the Graphs or Neighbor objects +#' \code{compute.SNN}. When running on a \code{\link[SeuratObject]{Seurat}} object, this +#' returns the \code{\link[SeuratObject]{Seurat}} object with the Graphs or Neighbor objects #' stored in their respective slots. Names of the Graph or Neighbor object can -#' be found with \code{\link{Graphs}} or \code{\link{Neighbors}}. +#' be found with \code{\link[SeuratObject]{Graphs}} or \code{\link[SeuratObject]{Neighbors}}. #' #' @examples #' data("pbmc_small") @@ -277,7 +277,7 @@ GetAssay <- function(object, ...) { #' @param reductions Name of reductions to be integrated. For a #' TransferAnchorSet, this should be the name of a reduction present in the #' anchorset object (for example, "pcaproject"). For an IntegrationAnchorSet, -#' this should be a \code{\link{DimReduc}} object containing all cells present +#' this should be a \code{\link[SeuratObject]{DimReduc}} object containing all cells present #' in the anchorset object. #' @param dims.to.integrate Number of dimensions to return integrated values for #' @param weight.reduction Dimension reduction to use when calculating anchor @@ -287,7 +287,7 @@ GetAssay <- function(object, ...) { #' all objects to be integrated} #' \item{A vector of strings, specifying the name of a dimension reduction to #' use for each object to be integrated} -#' \item{A vector of \code{\link{DimReduc}} objects, specifying the object to +#' \item{A vector of \code{\link[SeuratObject]{DimReduc}} objects, specifying the object to #' use for each object in the integration} #' \item{NULL, in which case the full corrected space is used for computing #' anchor weights.} @@ -470,7 +470,7 @@ PseudobulkExpression <- function(object, ...) { #' #' @return Returns a combined Seurat object with the CCA results stored. #' -#' @seealso \code{\link{merge.Seurat}} +#' @seealso \code{\link[SeuratObject]{merge.Seurat}} #' #' @examples #' \dontrun{ @@ -600,7 +600,7 @@ RunSLSI <- function(object, ...) { #' @references Barshan E, Ghodsi A, Azimifar Z, Jahromi MZ. #' Supervised principal component analysis: Visualization, classification and #' regression on subspaces and submanifolds. -#' Pattern Recognition. 2011 Jul 1;44(7):1357-71. \url{https://www.sciencedirect.com/science/article/pii/S0031320310005819?casa_token=AZMFg5OtPnAAAAAA:_Udu7GJ7G2ed1-XSmr-3IGSISUwcHfMpNtCj-qacXH5SBC4nwzVid36GXI3r8XG8dK5WOQui}; +#' Pattern Recognition. 2011 Jul 1;44(7):1357-71. \url{doi:10.1016/j.patcog.2010.12.015}; #' @export #' #' @rdname RunSPCA diff --git a/R/integration.R b/R/integration.R index 8ef4d47d1..8efd4c636 100644 --- a/R/integration.R +++ b/R/integration.R @@ -634,8 +634,8 @@ ReciprocalProject <- function( #' these scores to dampen outlier effects and rescale to range between 0-1.} #' } #' -#' @param reference \code{\link{Seurat}} object to use as the reference -#' @param query \code{\link{Seurat}} object to use as the query +#' @param reference \code{\link[SeuratObject]{Seurat}} object to use as the reference +#' @param query \code{\link[SeuratObject]{Seurat}} object to use as the query #' @param reference.assay Name of the Assay to use from reference #' @param reference.neighbors Name of the Neighbor to use from the reference. #' Optionally enables reuse of precomputed neighbors. @@ -689,7 +689,7 @@ ReciprocalProject <- function( #' @param n.trees More trees gives higher precision when using annoy approximate #' nearest neighbor search #' @param eps Error bound on the neighbor finding algorithm (from -#' \code{\link{RANN}} or \code{\link{RcppAnnoy}}) +#' \code{\link[RANN]{RANN}} or \code{\link[RcppAnnoy]{RcppAnnoy}}) #' @param approx.pca Use truncated singular value decomposition to approximate #' PCA #' @param mapping.score.k Compute and store nearest k query neighbors in the @@ -1334,8 +1334,8 @@ GetTransferPredictions <- function(object, assay = "predictions", slot = "data", #' all objects to be integrated} #' \item{A vector of strings, specifying the name of a dimension reduction to #' use for each object to be integrated} -#' \item{A vector of \code{\link{DimReduc}} objects, specifying the object to -#' use for each object in the integration} +#' \item{A vector of \code{\link[SeuratObject]{DimReduc}} objects, +#' specifying the object to use for each object in the integration} #' \item{NULL, in which case a new PCA will be calculated and used to #' calculate anchor weights} #' } @@ -1364,11 +1364,11 @@ GetTransferPredictions <- function(object, assay = "predictions", slot = "data", #' @param preserve.order Do not reorder objects based on size for each pairwise #' integration. #' @param eps Error bound on the neighbor finding algorithm (from -#' \code{\link{RANN}}) +#' \code{\link[RANN]{RANN}}) #' @param verbose Print progress bars and output #' -#' @return Returns a \code{\link{Seurat}} object with a new integrated -#' \code{\link{Assay}}. If \code{normalization.method = "LogNormalize"}, the +#' @return Returns a \code{\link[SeuratObject]{Seurat}} object with a new integrated +#' \code{\link[SeuratObject]{Assay}}. If \code{normalization.method = "LogNormalize"}, the #' integrated data is returned to the \code{data} slot and can be treated as #' log-normalized, corrected data. If \code{normalization.method = "SCT"}, the #' integrated data is returned to the \code{scale.data} slot and can be treated @@ -2756,10 +2756,10 @@ MixingMetric <- function( #' anchor.features for efficiency in downstream processing. } #' } #' -#' @param object.list A list of \code{\link{Seurat}} objects to prepare for integration -#' @param assay The name of the \code{\link{Assay}} to use for integration. This can be a +#' @param object.list A list of \code{\link[SeuratObject]{Seurat}} objects to prepare for integration +#' @param assay The name of the \code{\link[SeuratObject]{Assay}} to use for integration. This can be a #' single name if all the assays to be integrated have the same name, or a character vector -#' containing the name of each \code{\link{Assay}} in each object to be integrated. The +#' containing the name of each \code{\link[SeuratObject]{Assay}} in each object to be integrated. The #' specified assays must have been normalized using \code{\link{SCTransform}}. #' If NULL (default), the current default assay for each object is used. #' @param anchor.features Can be either: @@ -2773,7 +2773,7 @@ MixingMetric <- function( #' the Pearson residual will be clipped to #' @param verbose Display output/messages #' -#' @return A list of \code{\link{Seurat}} objects with the appropriate \code{scale.data} slots +#' @return A list of \code{\link[SeuratObject]{Seurat}} objects with the appropriate \code{scale.data} slots #' containing only the required \code{anchor.features}. #' #' @importFrom pbapply pblapply @@ -3219,7 +3219,7 @@ SelectSCTIntegrationFeatures <- function( #' \item{lsiproject: Use the projected LSI used for anchor building} #' \item{pca: Use an internal PCA on the query only} #' \item{cca: Use the CCA used for anchor building} -#' \item{custom DimReduc: User provided \code{\link{DimReduc}} object +#' \item{custom DimReduc: User provided \code{\[SeuratObject]{DimReduc}} object #' computed on the query cells} #' } #' @param l2.norm Perform L2 normalization on the cell embeddings after @@ -3230,7 +3230,7 @@ SelectSCTIntegrationFeatures <- function( #' @param k.weight Number of neighbors to consider when weighting anchors #' @param sd.weight Controls the bandwidth of the Gaussian kernel for weighting #' @param eps Error bound on the neighbor finding algorithm (from -#' \code{\link{RANN}}) +#' \code{\link[RANN]{RANN}}) #' @param n.trees More trees gives higher precision when using annoy approximate #' nearest neighbor search #' @param verbose Print progress bars and output @@ -4599,7 +4599,7 @@ GetCellOffsets <- function(anchors, dataset, cell, cellnames.list, cellnames) { # query, and weights will need to be calculated for all cells in the object. # @param sd.weight Controls the bandwidth of the Gaussian kernel for weighting # @param preserve.order Do not reorder objects based on size for each pairwise integration. -# @param eps Error bound on the neighbor finding algorithm (from \code{\link{RANN}}) +# @param eps Error bound on the neighbor finding algorithm (from \code{\link[RANN]{RANN}}) # @param verbose Print progress bars and output # # @return Returns an integrated matrix @@ -4742,7 +4742,7 @@ NNtoMatrix <- function(idx, distance, k) { # @param preserve.order Do not reorder objects based on size for each pairwise # integration. # @param eps Error bound on the neighbor finding algorithm (from -# \code{\link{RANN}}) +# \code{\link[RANN]{RANN}}) # @param verbose Print progress bars and output # # @return Returns a Seurat object with a new integrated Assay @@ -5497,7 +5497,7 @@ ReferenceRange <- function(x, lower = 0.025, upper = 0.975) { # query, and weights will need to be calculated for all cells in the object. # @param sd.weight Controls the bandwidth of the Gaussian kernel for weighting # @param sample.tree Specify the order of integration. If NULL, will compute automatically. -# @param eps Error bound on the neighbor finding algorithm (from \code{\link{RANN}}) +# @param eps Error bound on the neighbor finding algorithm (from \code{\link[RANN]{RANN}}) # @param verbose Print progress bars and output # RunIntegration <- function( diff --git a/R/integration5.R b/R/integration5.R index c0b7034d7..62d6d937e 100644 --- a/R/integration5.R +++ b/R/integration5.R @@ -288,7 +288,7 @@ attr(x = CCAIntegration, which = 'Seurat.method') <- 'integration' #' @param object A \code{Seurat} object #' @param assay Name of \code{Assay} in the \code{Seurat} object #' @param layers Names of layers in \code{assay} -#' @param orig A \link[SeuratObject:DimReduc]{dimensional reduction} to correct +#' @param orig A \link[SeuratObject]{DimReduc} to correct #' @param new.reduction Name of new integrated dimensional reduction #' @param reference A reference \code{Seurat} object #' @param features A vector of features to use for integration diff --git a/R/objects.R b/R/objects.R index 86b9ae482..50addbbfe 100644 --- a/R/objects.R +++ b/R/objects.R @@ -188,7 +188,7 @@ IntegrationData <- setClass( #' @slot arguments other information used in SCTransform #' @slot median_umi Median UMI (or scale factor) used to calculate corrected counts #' -#' @seealso \code{\link{Assay}} +#' @seealso \code{\link[SeuratObject]{Assay}} #' #' @name SCTAssay-class #' @rdname SCTAssay-class @@ -215,12 +215,12 @@ SCTModel <- setClass( #' The SCTAssay Class #' -#' The SCTAssay object contains all the information found in an \code{\link{Assay}} +#' The SCTAssay object contains all the information found in an \code{\link[SeuratObject]{Assay}} #' object, with extra information from the results of \code{\link{SCTransform}} #' #' @slot SCTModel.list A list containing SCT models #' -#' @seealso \code{\link{Assay}} +#' @seealso \code{\link[SeuratObject]{Assay}} #' #' @name SCTAssay-class #' @rdname SCTAssay-class @@ -904,7 +904,7 @@ TopCells <- function(object, dim = 1, ncells = 20, balanced = FALSE, ...) { #' #' Return a vector of cell names of the nearest n cells. #' -#' @param object \code{\link{Neighbor}} object +#' @param object \code{\link[SeuratObject]{Neighbor}} object #' @param cell Cell of interest #' @param n Number of neighbors to return #' diff --git a/R/visualization.R b/R/visualization.R index 64e5c9a52..65ef5c94a 100644 --- a/R/visualization.R +++ b/R/visualization.R @@ -6320,9 +6320,9 @@ WhiteBackground <- function(...) { #' Prepare Coordinates for Spatial Plots #' #' @inheritParams SeuratObject::GetTissueCoordinates -#' @param model A \code{\linkS4class{Segmentation}}, -#' \code{\linkS4class{Centroids}}, -#' or \code{\linkS4class{Molecules}} object +#' @param model A \code{\link[SeuratObject:Segmentation-class]{Segmentation}}, +#' \code{\link[SeuratObject:Centroids-class]{Centroids}}, +#' or \code{\link[SeuratObject:Molecules-class]{Molecules}} object #' @param data Extra data to be used for annotating the cell segmentations; the #' easiest way to pass data is a one-column #' \code{\link[base:data.frame]{data frame}} with the values to color by and diff --git a/cran-comments.md b/cran-comments.md index 09e951b1f..fed512508 100644 --- a/cran-comments.md +++ b/cran-comments.md @@ -1,31 +1,34 @@ -# Seurat v5.1.0 +# Seurat v5.2.0 ## Test environments -* local ubuntu 20.04 install, R 4.3.2 -* local macOS 14.1, R 4.4.0 +* local ubuntu 20.04 install, R 4.4.2 * win-builder (oldrelease, release, devel) +* mac-builder (devel) + +We were unable to test on r-release on mac-builder because the portal seemed to point to the wrong version. ## R CMD check results There were no ERRORs or WARNINGs -There were two NOTEs - -> Suggests or Enhances not in mainstream repositories: -> BPCells, presto -> Availability using Additional_repositories specification: -> BPCells yes https://bnprks.r-universe.dev -> presto yes https://satijalab.r-universe.dev +There was one NOTE -> * checking package dependencies ... NOTE -> Package suggested but not available for checking: 'BPCells', 'presto' +❯ checking CRAN incoming feasibility ... [12s/61s] NOTE + Maintainer: ‘Rahul Satija ’ + + Suggests or Enhances not in mainstream repositories: + BPCells, enrichR, presto + Availability using Additional_repositories specification: + BPCells yes https://bnprks.r-universe.dev + enrichR yes https://cran.r-universe.dev + presto yes https://satijalab.r-universe.dev -BPCells and presto are hosted on R-universe and used conditionally in Seurat. +BPCells, enrichR, and presto are hosted on R-universe and used conditionally in Seurat. ## Downstream dependencies -There are three packages that depend on Seurat: CACIMAR, scCustomize, and SCdeconR; this update does not impact their functionality +There are 3 packages that depend on Seurat: CACIMAR, scCustomize, and SCdeconR; this update does not impact their functionality. -There are 30 packages that import Seurat: AnanseSeurat, APackOfTheClones, bbknnR, CAMML, DR.SC, DWLS, GeneNMF, ggsector, mixhvg, nebula, Platypus, PRECAST, ProFAST, rPanglaoDB, scAnnotate, scaper, sccca, scDiffCom, scGate, scGOclust, scMappR, scperturbR, scpoisson, SCRIP, scRNAstat, SignacX, SoupX, SPECK, STREAK, and tidyseurat; this update does not impact their functionality +There are 34 packages that import Seurat: AnanseSeurat, APackOfTheClones, bbknnR, CAESAR.Suite, CAMML, DR.SC, DWLS, GeneNMF, ggsector, mixhvg, nebula, Platypus, PoweREST, PRECAST, ProFAST, rPanglaoDB, scAnnotate, scaper, sccca, scDiffCom, scGate, scGOclust, SCIntRuler, scMappR, scperturbR, scpoisson, SCRIP, scRNAstat, SignacX, SoupX, SpaCCI, SPECK, STREAK, and tidyseurat; this update does not impact their functionality. -There are 22 packages that suggest Seurat: BisqueRNA, Canek, cellpypes, CIARA, ClustAssess, clustree, combiroc, conos, countland, CRMetrics, CytoSimplex, DIscBIO, dyngen, grandR, harmony, RESET, rliger, SCORPIUS, SCpubr, Signac, treefit, and VAM; this update does not impact their functionality +There are 27 packages that suggest Seurat: BisqueRNA, Canek, cellpypes, CIARA, ClustAssess, clustree, combiroc, conos, countland, CRMetrics, CytoSimplex, DIscBIO, dyngen, easybio, grandR, harmony, laminr, mxfda, RESET, rliger, SCORPIUS, SCpubr, scregclust, Signac, SuperCell, treefit, and VAM; this update does not impact their functionality. diff --git a/man/CCAIntegration.Rd b/man/CCAIntegration.Rd index b8399ad04..f4f1e5b0a 100644 --- a/man/CCAIntegration.Rd +++ b/man/CCAIntegration.Rd @@ -33,7 +33,7 @@ CCAIntegration( \item{layers}{Names of layers in \code{assay}} -\item{orig}{A \link[SeuratObject:DimReduc]{dimensional reduction} to correct} +\item{orig}{A \link[SeuratObject]{DimReduc} to correct} \item{new.reduction}{Name of new integrated dimensional reduction} @@ -61,7 +61,7 @@ weights. This can be one of: all objects to be integrated} \item{A vector of strings, specifying the name of a dimension reduction to use for each object to be integrated} - \item{A vector of \code{\link{DimReduc}} objects, specifying the object to + \item{A vector of \code{\link[SeuratObject]{DimReduc}} objects, specifying the object to use for each object in the integration} \item{NULL, in which case the full corrected space is used for computing anchor weights.} diff --git a/man/FindNeighbors.Rd b/man/FindNeighbors.Rd index 0c4b8c703..de80c0ab5 100644 --- a/man/FindNeighbors.Rd +++ b/man/FindNeighbors.Rd @@ -98,7 +98,7 @@ be set automatically} \item{k.param}{Defines k for the k-nearest neighbor algorithm} -\item{return.neighbor}{Return result as \code{\link{Neighbor}} object. Not +\item{return.neighbor}{Return result as \code{\link[SeuratObject]{Neighbor}} object. Not used with distance matrix input.} \item{compute.SNN}{also compute the shared nearest neighbor graph} @@ -152,13 +152,13 @@ neighbor (NN) graph, and the second element used to store the SNN graph. If only one name is supplied, only the NN graph is stored.} } \value{ -This function can either return a \code{\link{Neighbor}} object -with the KNN information or a list of \code{\link{Graph}} objects with +This function can either return a \code{\link[SeuratObject]{Neighbor}} object +with the KNN information or a list of \code{\link[SeuratObject]{Graph}} objects with the KNN and SNN depending on the settings of \code{return.neighbor} and -\code{compute.SNN}. When running on a \code{\link{Seurat}} object, this -returns the \code{\link{Seurat}} object with the Graphs or Neighbor objects +\code{compute.SNN}. When running on a \code{\link[SeuratObject]{Seurat}} object, this +returns the \code{\link[SeuratObject]{Seurat}} object with the Graphs or Neighbor objects stored in their respective slots. Names of the Graph or Neighbor object can -be found with \code{\link{Graphs}} or \code{\link{Neighbors}}. +be found with \code{\link[SeuratObject]{Graphs}} or \code{\link[SeuratObject]{Neighbors}}. } \description{ Computes the \code{k.param} nearest neighbors for a given dataset. Can also diff --git a/man/FindTransferAnchors.Rd b/man/FindTransferAnchors.Rd index f0dfbbc60..4ea81c058 100644 --- a/man/FindTransferAnchors.Rd +++ b/man/FindTransferAnchors.Rd @@ -33,9 +33,9 @@ FindTransferAnchors( ) } \arguments{ -\item{reference}{\code{\link{Seurat}} object to use as the reference} +\item{reference}{\code{\link[SeuratObject]{Seurat}} object to use as the reference} -\item{query}{\code{\link{Seurat}} object to use as the query} +\item{query}{\code{\link[SeuratObject]{Seurat}} object to use as the query} \item{normalization.method}{Name of normalization method used: LogNormalize or SCT.} @@ -109,7 +109,7 @@ annoy} nearest neighbor search} \item{eps}{Error bound on the neighbor finding algorithm (from -\code{\link{RANN}} or \code{\link{RcppAnnoy}})} +\code{\link[RANN]{RANN}} or \code{\link[RcppAnnoy]{RcppAnnoy}})} \item{approx.pca}{Use truncated singular value decomposition to approximate PCA} diff --git a/man/IntegrateData.Rd b/man/IntegrateData.Rd index e08bd682e..399fdc3fc 100644 --- a/man/IntegrateData.Rd +++ b/man/IntegrateData.Rd @@ -47,8 +47,8 @@ weights. This can be one of: all objects to be integrated} \item{A vector of strings, specifying the name of a dimension reduction to use for each object to be integrated} -\item{A vector of \code{\link{DimReduc}} objects, specifying the object to -use for each object in the integration} +\item{A vector of \code{\link[SeuratObject]{DimReduc}} objects, +specifying the object to use for each object in the integration} \item{NULL, in which case a new PCA will be calculated and used to calculate anchor weights} } @@ -80,13 +80,13 @@ If NULL, the sample tree will be computed automatically.} integration.} \item{eps}{Error bound on the neighbor finding algorithm (from -\code{\link{RANN}})} +\code{\link[RANN]{RANN}})} \item{verbose}{Print progress bars and output} } \value{ -Returns a \code{\link{Seurat}} object with a new integrated -\code{\link{Assay}}. If \code{normalization.method = "LogNormalize"}, the +Returns a \code{\link[SeuratObject]{Seurat}} object with a new integrated +\code{\link[SeuratObject]{Assay}}. If \code{normalization.method = "LogNormalize"}, the integrated data is returned to the \code{data} slot and can be treated as log-normalized, corrected data. If \code{normalization.method = "SCT"}, the integrated data is returned to the \code{scale.data} slot and can be treated diff --git a/man/IntegrateEmbeddings.Rd b/man/IntegrateEmbeddings.Rd index 304d0500a..61a185f92 100644 --- a/man/IntegrateEmbeddings.Rd +++ b/man/IntegrateEmbeddings.Rd @@ -49,7 +49,7 @@ IntegrateEmbeddings(anchorset, ...) \item{reductions}{Name of reductions to be integrated. For a TransferAnchorSet, this should be the name of a reduction present in the anchorset object (for example, "pcaproject"). For an IntegrationAnchorSet, -this should be a \code{\link{DimReduc}} object containing all cells present +this should be a \code{\link[SeuratObject]{DimReduc}} object containing all cells present in the anchorset object.} \item{dims.to.integrate}{Number of dimensions to return integrated values for} @@ -63,7 +63,7 @@ weights. This can be one of: all objects to be integrated} \item{A vector of strings, specifying the name of a dimension reduction to use for each object to be integrated} - \item{A vector of \code{\link{DimReduc}} objects, specifying the object to + \item{A vector of \code{\link[SeuratObject]{DimReduc}} objects, specifying the object to use for each object in the integration} \item{NULL, in which case the full corrected space is used for computing anchor weights.} diff --git a/man/JointPCAIntegration.Rd b/man/JointPCAIntegration.Rd index 3f2ab73f7..a390c1f23 100644 --- a/man/JointPCAIntegration.Rd +++ b/man/JointPCAIntegration.Rd @@ -33,7 +33,7 @@ JointPCAIntegration( \item{layers}{Names of layers in \code{assay}} -\item{orig}{A \link[SeuratObject:DimReduc]{dimensional reduction} to correct} +\item{orig}{A \link[SeuratObject]{DimReduc} to correct} \item{new.reduction}{Name of new integrated dimensional reduction} @@ -61,7 +61,7 @@ weights. This can be one of: all objects to be integrated} \item{A vector of strings, specifying the name of a dimension reduction to use for each object to be integrated} - \item{A vector of \code{\link{DimReduc}} objects, specifying the object to + \item{A vector of \code{\link[SeuratObject]{DimReduc}} objects, specifying the object to use for each object in the integration} \item{NULL, in which case the full corrected space is used for computing anchor weights.} diff --git a/man/PrepSCTIntegration.Rd b/man/PrepSCTIntegration.Rd index d3fdecae4..8052e10e2 100644 --- a/man/PrepSCTIntegration.Rd +++ b/man/PrepSCTIntegration.Rd @@ -13,11 +13,11 @@ PrepSCTIntegration( ) } \arguments{ -\item{object.list}{A list of \code{\link{Seurat}} objects to prepare for integration} +\item{object.list}{A list of \code{\link[SeuratObject]{Seurat}} objects to prepare for integration} -\item{assay}{The name of the \code{\link{Assay}} to use for integration. This can be a +\item{assay}{The name of the \code{\link[SeuratObject]{Assay}} to use for integration. This can be a single name if all the assays to be integrated have the same name, or a character vector -containing the name of each \code{\link{Assay}} in each object to be integrated. The +containing the name of each \code{\link[SeuratObject]{Assay}} in each object to be integrated. The specified assays must have been normalized using \code{\link{SCTransform}}. If NULL (default), the current default assay for each object is used.} @@ -35,7 +35,7 @@ the Pearson residual will be clipped to} \item{verbose}{Display output/messages} } \value{ -A list of \code{\link{Seurat}} objects with the appropriate \code{scale.data} slots +A list of \code{\link[SeuratObject]{Seurat}} objects with the appropriate \code{scale.data} slots containing only the required \code{anchor.features}. } \description{ diff --git a/man/RPCAIntegration.Rd b/man/RPCAIntegration.Rd index 0e4589d68..3c93933c2 100644 --- a/man/RPCAIntegration.Rd +++ b/man/RPCAIntegration.Rd @@ -33,7 +33,7 @@ RPCAIntegration( \item{layers}{Names of layers in \code{assay}} -\item{orig}{A \link[SeuratObject:DimReduc]{dimensional reduction} to correct} +\item{orig}{A \link[SeuratObject]{DimReduc} to correct} \item{new.reduction}{Name of new integrated dimensional reduction} @@ -61,7 +61,7 @@ weights. This can be one of: all objects to be integrated} \item{A vector of strings, specifying the name of a dimension reduction to use for each object to be integrated} - \item{A vector of \code{\link{DimReduc}} objects, specifying the object to + \item{A vector of \code{\link[SeuratObject]{DimReduc}} objects, specifying the object to use for each object in the integration} \item{NULL, in which case the full corrected space is used for computing anchor weights.} diff --git a/man/RunCCA.Rd b/man/RunCCA.Rd index aa2c6b14b..71091ba23 100644 --- a/man/RunCCA.Rd +++ b/man/RunCCA.Rd @@ -91,6 +91,6 @@ print(x = pbmc_cca[["cca"]]) } \seealso{ -\code{\link{merge.Seurat}} +\code{\link[SeuratObject]{merge.Seurat}} } \concept{dimensional_reduction} diff --git a/man/RunSPCA.Rd b/man/RunSPCA.Rd index 11c23986e..87fb7efa3 100644 --- a/man/RunSPCA.Rd +++ b/man/RunSPCA.Rd @@ -99,6 +99,6 @@ matrix factorization. Barshan E, Ghodsi A, Azimifar Z, Jahromi MZ. Supervised principal component analysis: Visualization, classification and regression on subspaces and submanifolds. -Pattern Recognition. 2011 Jul 1;44(7):1357-71. \url{https://www.sciencedirect.com/science/article/pii/S0031320310005819?casa_token=AZMFg5OtPnAAAAAA:_Udu7GJ7G2ed1-XSmr-3IGSISUwcHfMpNtCj-qacXH5SBC4nwzVid36GXI3r8XG8dK5WOQui}; +Pattern Recognition. 2011 Jul 1;44(7):1357-71. \url{doi:10.1016/j.patcog.2010.12.015}; } \concept{dimensional_reduction} diff --git a/man/SCTAssay-class.Rd b/man/SCTAssay-class.Rd index d116a62e9..5feba288a 100644 --- a/man/SCTAssay-class.Rd +++ b/man/SCTAssay-class.Rd @@ -27,7 +27,7 @@ The SCTModel object is a model and parameters storage from SCTransform. It can be used to calculate Pearson residuals for new genes. -The SCTAssay object contains all the information found in an \code{\link{Assay}} +The SCTAssay object contains all the information found in an \code{\link[SeuratObject]{Assay}} object, with extra information from the results of \code{\link{SCTransform}} } \section{Slots}{ @@ -93,8 +93,8 @@ levels(pbmc_small[['SCT']]) } \seealso{ -\code{\link{Assay}} +\code{\link[SeuratObject]{Assay}} -\code{\link{Assay}} +\code{\link[SeuratObject]{Assay}} } \concept{objects} diff --git a/man/TopNeighbors.Rd b/man/TopNeighbors.Rd index 64dc5cc67..1c029803a 100644 --- a/man/TopNeighbors.Rd +++ b/man/TopNeighbors.Rd @@ -7,7 +7,7 @@ TopNeighbors(object, cell, n = 5) } \arguments{ -\item{object}{\code{\link{Neighbor}} object} +\item{object}{\code{\link[SeuratObject]{Neighbor}} object} \item{cell}{Cell of interest} diff --git a/man/TransferData.Rd b/man/TransferData.Rd index e30977df7..4df588c51 100644 --- a/man/TransferData.Rd +++ b/man/TransferData.Rd @@ -53,7 +53,7 @@ anchors. Options are: \item{lsiproject: Use the projected LSI used for anchor building} \item{pca: Use an internal PCA on the query only} \item{cca: Use the CCA used for anchor building} - \item{custom DimReduc: User provided \code{\link{DimReduc}} object + \item{custom DimReduc: User provided \code{\[SeuratObject]{DimReduc}} object computed on the query cells} }} @@ -69,7 +69,7 @@ weighting.} \item{sd.weight}{Controls the bandwidth of the Gaussian kernel for weighting} \item{eps}{Error bound on the neighbor finding algorithm (from -\code{\link{RANN}})} +\code{\link[RANN]{RANN}})} \item{n.trees}{More trees gives higher precision when using annoy approximate nearest neighbor search} diff --git a/man/fortify-Spatial.Rd b/man/fortify-Spatial.Rd index e2d13bcf8..b19fea1b6 100644 --- a/man/fortify-Spatial.Rd +++ b/man/fortify-Spatial.Rd @@ -15,9 +15,9 @@ \method{fortify}{Segmentation}(model, data, ...) } \arguments{ -\item{model}{A \code{\linkS4class{Segmentation}}, -\code{\linkS4class{Centroids}}, -or \code{\linkS4class{Molecules}} object} +\item{model}{A \code{\link[SeuratObject:Segmentation-class]{Segmentation}}, +\code{\link[SeuratObject:Centroids-class]{Centroids}}, +or \code{\link[SeuratObject:Molecules-class]{Molecules}} object} \item{data}{Extra data to be used for annotating the cell segmentations; the easiest way to pass data is a one-column