Update documents

NAMESPACE

@@ -106,7 +106,6 @@ export(MergeNode)
 export(MergeSeurat)
 export(MetageneBicorPlot)
 export(MinMax)
-export(MultiModal_CCA)
 export(NegBinomDETest)
 export(NegBinomRegDETest)
 export(NormalizeData)

R/multi_modal.R

@@ -221,19 +221,20 @@ CollapseSpeciesExpressionMatrix <- function(
 #'
 #' @param object Seurat object. Assumes that the hash tag oligo (HTO) data has been added and normalized.
 #' @param assay.type Name of the Hashtag assay (HTO by default)
-#' @param positive_quantile The quantile of inferred 'negative' distribution for each HTO - over which the cell is considered 'positive'. Default is 0.99
-#' @param init_centers Initial number of clusters for kmeans of the HTO oligos. Default is the # of hashtag oligo names + 1 (to account for negatives)
-#' @param k_function Clustering function for initial HTO grouping. Default is "clara" for fast k-medoids clustering on large applications, also support "kmeans" for kmeans clustering
+#' @param positive_quantile The quantile of inferred 'negative' distribution for each hashtag - over which the cell is considered 'positive'. Default is 0.99
+#' @param init_centers Initial number of clusters for hashtags. Default is the # of hashtag oligo names + 1 (to account for negatives)
+#' @param k_function Clustering function for initial hashtag grouping. Default is "clara" for fast k-medoids clustering on large applications, also support "kmeans" for kmeans clustering
 #' @param nsamples Number of samples to be drawn from the dataset used for clustering, for k_function = "clara"
 #' @param cluster_nstarts nstarts value for k-means clustering (for k_function = "kmeans"). 100 by default
 #' @param print.output Prints the output
+#' 
 #' @return The Seurat object with the following demultiplexed information stored in the meta data:
-#' @return hash_maxID Name of HTO with the highest signal.
-#' @return hash_secondID Name of HTO with the second highest signal
-#' @return hash_margin The difference between signals for hash_maxID and hash_secondID
-#' @return hto_classification Classification result, with doublets/multiplets named by the top two highest HTOs
-#' @return hto_classification_global Global classification result (singlet, doublet or negative)
-#' @return hash_ID Classification result where doublet IDs are collapsed
+#' \item{hash_maxID}{Name of hashtag with the highest signal}
+#' \item{hash_secondID}{Name of hashtag with the second highest signal}
+#' \item{hash_margin}{The difference between signals for hash_maxID and hash_secondID}
+#' \item{hto_classification}{Classification result, with doublets/multiplets named by the top two highest hashtags}
+#' \item{hto_classification_global}{Global classification result (singlet, doublet or negative)}
+#' \item{hash_ID}{Classification result where doublet IDs are collapsed}
 #'
 #' @importFrom stats pnbinom
 #' @importFrom cluster clara