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..20239e852 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{
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