From c6e75ad525b42dd4b8f8d37dc88b68e2cf075812 Mon Sep 17 00:00:00 2001 From: Tuomas Borman <60338854+TuomasBorman@users.noreply.github.com> Date: Mon, 3 Feb 2025 15:09:18 +0200 Subject: [PATCH] Update docs (#685) --- R/addAlpha.R | 19 +++++ R/addDissimilarity.R | 157 ++++++++++++++++++++++------------------ man/addAlpha.Rd | 20 +++++ man/addDivergence.Rd | 4 +- man/getDissimilarity.Rd | 48 ++++++++---- man/getDominant.Rd | 4 +- man/getPERMANOVA.Rd | 4 +- man/getPrevalence.Rd | 4 +- man/isContaminant.Rd | 4 +- man/meltSE.Rd | 4 +- man/mergeSEs.Rd | 4 +- man/rarefyAssay.Rd | 4 +- man/runCCA.Rd | 4 +- man/runDPCoA.Rd | 4 +- man/runNMDS.Rd | 4 +- man/transformAssay.Rd | 4 +- 16 files changed, 185 insertions(+), 107 deletions(-) diff --git a/R/addAlpha.R b/R/addAlpha.R index 927424079..d67afa7d2 100644 --- a/R/addAlpha.R +++ b/R/addAlpha.R @@ -325,6 +325,21 @@ #' #' } #' +#' ## Rarefaction +#' +#' Rarefaction can be used to control uneven sequencing depths. Although, +#' it is highly debated method. Some think that it is the only option that +#' successfully controls the variation caused by uneven sampling depths. +#' The biggest argument against rarefaction is the fact that it omits data. +#' +#' Rarefaction works by sampling the counts randomly. This random sampling +#' is done \code{niter} times. In each sampling iteration, \code{sample} number +#' of random samples are drawn, and alpha diversity is calculated for this +#' subset. After the iterative process, there are \code{niter} number of +#' result that are then averaged to get the final result. +#' +#' Refer to Schloss (2024) for more details on rarefaction. +#' #' @references #' #' Beisel J-N. et al. (2003) @@ -394,6 +409,10 @@ #' The measurement of diversity in different types of #' biological collections. _J Theoretical Biology_ 13:131--144. #' +#' Schloss PD (2024) Rarefaction is currently the best approach to control for +#' uneven sequencing effort in amplicon sequence analyses. _mSphere_ +#' 28;9(2):e0035423. doi: 10.1128/msphere.00354-23 +#' #' Simpson EH (1949) #' Measurement of Diversity. #' _Nature_ 163(688). doi: 10.1038/163688a0 diff --git a/R/addDissimilarity.R b/R/addDissimilarity.R index 725d57f93..15df90f10 100644 --- a/R/addDissimilarity.R +++ b/R/addDissimilarity.R @@ -1,107 +1,111 @@ #' Calculate dissimilarities #' -#' These functions are designed to calculate dissimilarities on data stored -#' within a +#' These functions are designed to calculate dissimilarities on data stored +#' within a #' \code{\link[TreeSummarizedExperiment:TreeSummarizedExperiment-class]{TreeSummarizedExperiment}} -#' object. For overlap, Unifrac, and Jensen-Shannon Divergence (JSD) -#' dissimilarities, the functions use mia internal functions, while for other +#' object. For overlap, Unifrac, and Jensen-Shannon Divergence (JSD) +#' dissimilarities, the functions use mia internal functions, while for other #' types of dissimilarities, they rely on \code{\link[vegan:vegdist]{vegdist}} #' by default. #' +#' @inheritParams addAlpha +#' #' @param x #' \code{\link[TreeSummarizedExperiment:TreeSummarizedExperiment-class]{TreeSummarizedExperiment}} #' or \code{matrix}. #' -#' @param method \code{Character scalar}. Specifies which dissimilarity to +#' @param method \code{Character scalar}. Specifies which dissimilarity to #' calculate. (Default: \code{"bray"}) -#' -#' @param name \code{Character scalar}. The name to be used to store the result +#' +#' @param name \code{Character scalar}. The name to be used to store the result #' in metadata of the output. (Default: \code{method}) #' -#' @param assay.type \code{Character scalar}. Specifies which assay to use for -#' calculation. (Default: \code{"counts"}) -#' -#' @param niter The number of iterations performed. If \code{NULL}, -#' rarefaction is disabled. (Default: \code{NULL}) -#' #' @param transposed \code{Logical scalar}. Specifies if x is transposed with #' cells in rows. (Default: \code{FALSE}) #' #' @param ... other arguments passed into \code{\link[vegan:avgdist]{avgdist}}, #' \code{\link[vegan:vegdist]{vegdist}}, or into mia internal functions: -#' +#' #' \itemize{ #' \item \code{sample}: The sampling depth in rarefaction. #' (Default: \code{min(rowSums2(x))}) -#' +#' #' \item \code{dis.fun}: \code{Character scalar}. Specifies the dissimilarity #' function to be used. -#' +#' #' \item \code{tree.name}: (Unifrac) \code{Character scalar}. Specifies the #' name of the tree from \code{rowTree(x)} that is used in calculation. #' Disabled when \code{tree} is specified. (Default: \code{"phylo"}) -#' +#' #' \item \code{tree}: (Unifrac) \code{phylo}. A phylogenetic tree used in #' calculation. (Default: \code{NULL}) -#' +#' #' \item \code{weighted}: (Unifrac) \code{Logical scalar}. Should use -#' weighted-Unifrac calculation? +#' weighted-Unifrac calculation? #' Weighted-Unifrac takes into account the relative abundance of #' species/taxa shared between samples, whereas unweighted-Unifrac only #' considers presence/absence. Default is \code{FALSE}, meaning the #' unweighted-Unifrac dissimilarity is calculated for all pairs of samples. #' (Default: \code{FALSE}) -#' +#' #' \item \code{node.label} (Unifrac) \code{character vector}. Used only if -#' \code{x} is a matrix. Specifies links between rows/columns and tips of -#' \code{tree}. The length must equal the number of rows/columns of \code{x}. +#' \code{x} is a matrix. Specifies links between rows/columns and tips of +#' \code{tree}. The length must equal the number of rows/columns of \code{x}. #' Furthermore, all the node labs must be present in \code{tree}. -#' +#' #' \item \code{chunkSize}: (JSD) \code{Integer scalar}. Defines the size of -#' data send to the individual worker. Only has an effect, if \code{BPPARAM} +#' data send to the individual worker. Only has an effect, if \code{BPPARAM} #' defines more than one worker. (Default: \code{nrow(x)}) -#' +#' #' \item \code{BPPARAM}: (JSD) #' \code{\link[BiocParallel:BiocParallelParam-class]{BiocParallelParam}}. #' Specifies whether the calculation should be parallelized. -#' +#' #' \item \code{detection}: (Overlap) \code{Numeric scalar}. -#' Defines detection threshold for absence/presence of features. Feature that -#' has abundance under threshold in either of samples, will be discarded when -#' evaluating overlap between samples. (Default: \code{0}) +#' Defines detection threshold for absence/presence of features. Feature that +#' has abundance under threshold in either of samples, will be discarded when +#' evaluating overlap between samples. (Default: \code{0}) #' } #' -#' @return +#' @return #' \code{getDissimilarity} returns a sample-by-sample dissimilarity matrix. -#' -#' \code{addDissimilarity} returns \code{x} that includes dissimilarity matrix -#' in its metadata. -#' -#' @details -#' Overlap reflects similarity between sample-pairs. When overlap is -#' calculated using relative abundances, the higher the value the higher the -#' similarity is. When using relative abundances, overlap value 1 means that -#' all the abundances of features are equal between two samples, and 0 means -#' that samples have completely different relative abundances. -#' +#' +#' \code{addDissimilarity} returns \code{x} that includes dissimilarity matrix +#' in its metadata. +#' +#' @details +#' Overlap reflects similarity between sample-pairs. When overlap is +#' calculated using relative abundances, the higher the value the higher the +#' similarity is. When using relative abundances, overlap value 1 means that +#' all the abundances of features are equal between two samples, and 0 means +#' that samples have completely different relative abundances. +#' #' Unifrac is calculated with \code{\link[rbiom:unifrac]{rbiom:unifrac()}}. -#' +#' #' If rarefaction is enabled, \code{\link[vegan:avgdist]{vegan:avgdist()}} is #' utilized. -#' -#' For JSD implementation: -#' Susan Holmes \email{susan@@stat.stanford.edu}. -#' Adapted for phyloseq by Paul J. McMurdie. -#' Adapted for mia by Felix G.M. Ernst -#' +#' +#' Rarefaction can be used to control uneven sequencing depths. Although, +#' it is highly debated method. Some think that it is the only option that +#' successfully controls the variation caused by uneven sampling depths. +#' The biggest argument against rarefaction is the fact that it omits data. +#' +#' Rarefaction works by sampling the counts randomly. This random sampling +#' is done \code{niter} times. In each sampling iteration, \code{sample} number +#' of random samples are drawn, and dissimilarity is calculated for this +#' subset. After the iterative process, there are \code{niter} number of +#' result that are then averaged to get the final result. +#' +#' Refer to Schloss (2024) for more details on rarefaction. +#' #' @name getDissimilarity -#' +#' #' @seealso #' \url{http://en.wikipedia.org/wiki/Jensen-Shannon_divergence} -#' +#' #' @references #' For unifrac dissimilarity: \url{http://bmf.colorado.edu/unifrac/} -#' +#' #' See also additional descriptions of Unifrac in the following articles: #' #' Lozupone, Hamady and Knight, ``Unifrac - An Online Tool for Comparing @@ -114,46 +118,59 @@ #' #' Lozupone C, Knight R. ``Unifrac: a new phylogenetic method for comparing #' microbial communities.'' Appl Environ Microbiol. 2005 71 (12):8228-35. -#' -#' For JSD dissimilarity: +#' +#' For JSD dissimilarity: #' Jensen-Shannon Divergence and Hilbert space embedding. #' Bent Fuglede and Flemming Topsoe University of Copenhagen, #' Department of Mathematics #' \url{http://www.math.ku.dk/~topsoe/ISIT2004JSD.pdf} #' +#' For rarefaction: +#' Schloss PD (2024) Rarefaction is currently the best approach to control for +#' uneven sequencing effort in amplicon sequence analyses. _mSphere_ +#' 28;9(2):e0035423. doi: 10.1128/msphere.00354-23 +#' #' @export #' #' @examples #' library(mia) #' library(scater) -#' +#' #' # load dataset #' data(GlobalPatterns) #' tse <- GlobalPatterns -#' +#' #' ### Overlap dissimilarity -#' +#' #' tse <- addDissimilarity(tse, method = "overlap", detection = 0.25) #' metadata(tse)[["overlap"]][1:6, 1:6] -#' +#' #' ### JSD dissimilarity -#' +#' #' tse <- addDissimilarity(tse, method = "jsd") #' metadata(tse)[["jsd"]][1:6, 1:6] -#' +#' #' # Multi Dimensional Scaling applied to JSD dissimilarity matrix -#' tse <- runMDS(tse, FUN = getDissimilarity, method = "overlap", -#' assay.type = "counts") -#' metadata(tse)[["MDS"]][1:6, ] -#' +#' tse <- runMDS( +#' tse, FUN = getDissimilarity, method = "overlap", assay.type = "counts") +#' reducedDim(tse, "MDS") |> head() +#' #' ### Unifrac dissimilarity -#' +#' #' res <- getDissimilarity(tse, method = "unifrac", weighted = FALSE) -#' dim(as.matrix((res))) -#' +#' dim(as.matrix(res)) +#' #' tse <- addDissimilarity(tse, method = "unifrac", weighted = TRUE) #' metadata(tse)[["unifrac"]][1:6, 1:6] -#' +#' +#' ### Bray dissimilarity +#' +#' # Bray is usually applied to relative abundances so we have to apply +#' # transformation first +#' tse <- transformAssay(tse, method = "relabundance") +#' res <- getDissimilarity(tse, method = "bray", assay.type = "relabundance") +#' as.matrix(res)[1:6, 1:6] +#' NULL #' @rdname getDissimilarity @@ -269,7 +286,7 @@ setMethod( # sample is only used when niter is specified if( !is.null(niter) && !.is_an_integer(sample) ){ stop("'sample' must be an integer.", call. = FALSE) - } + } # # If the dissimilarity function is not specified, get default choice if( is.null(dis.fun) ){ @@ -324,7 +341,7 @@ setMethod( } tree_args <- list(x = mat, tree = tree) } else{ - tree_args <- .get_tree_args_from_TreeSE(x, transposed = transposed, + tree_args <- .get_tree_args_from_TreeSE(x, transposed = transposed, assay.type = assay.type, ...) } args <- c(args, tree_args) @@ -364,7 +381,7 @@ setMethod( links <- links_FUN(x) links <- links[ , "nodeLab"] node.label <- links - + # Get assay. By default, dissimilarity between samples is calculated. In # dissimilarity functions, features must be in columns and samples in rows # in this case. diff --git a/man/addAlpha.Rd b/man/addAlpha.Rd index 4f431db44..93b5b9185 100644 --- a/man/addAlpha.Rd +++ b/man/addAlpha.Rd @@ -360,6 +360,22 @@ corresponding index in the \pkg{vegan} package is "richness". } } + +\subsection{Rarefaction}{ + +Rarefaction can be used to control uneven sequencing depths. Although, +it is highly debated method. Some think that it is the only option that +successfully controls the variation caused by uneven sampling depths. +The biggest argument against rarefaction is the fact that it omits data. + +Rarefaction works by sampling the counts randomly. This random sampling +is done \code{niter} times. In each sampling iteration, \code{sample} number +of random samples are drawn, and alpha diversity is calculated for this +subset. After the iterative process, there are \code{niter} number of +result that are then averaged to get the final result. + +Refer to Schloss (2024) for more details on rarefaction. +} } \examples{ @@ -456,6 +472,10 @@ Pielou, EC. (1966) The measurement of diversity in different types of biological collections. \emph{J Theoretical Biology} 13:131--144. +Schloss PD (2024) Rarefaction is currently the best approach to control for +uneven sequencing effort in amplicon sequence analyses. \emph{mSphere} +28;9(2):e0035423. doi: 10.1128/msphere.00354-23 + Simpson EH (1949) Measurement of Diversity. \emph{Nature} 163(688). doi: 10.1038/163688a0 diff --git a/man/addDivergence.Rd b/man/addDivergence.Rd index 8d73661ca..9606444db 100644 --- a/man/addDivergence.Rd +++ b/man/addDivergence.Rd @@ -44,8 +44,8 @@ values are used to calculate divergence instead of the assay. Can be disabled with \code{NULL}. (Default: \code{NULL}) }} -\item{assay.type}{\code{Character scalar}. Specifies which assay to use for -calculation. (Default: \code{"counts"})} +\item{assay.type}{\code{Character scalar}. Specifies the name of assay +used in calculation. (Default: \code{"counts"})} \item{assay_name}{Deprecated. Use \code{assay.type} instead.} diff --git a/man/getDissimilarity.Rd b/man/getDissimilarity.Rd index 41cdfb8b3..f5ad7238a 100644 --- a/man/getDissimilarity.Rd +++ b/man/getDissimilarity.Rd @@ -89,11 +89,12 @@ evaluating overlap between samples. (Default: \code{0}) \item{name}{\code{Character scalar}. The name to be used to store the result in metadata of the output. (Default: \code{method})} -\item{assay.type}{\code{Character scalar}. Specifies which assay to use for -calculation. (Default: \code{"counts"})} +\item{assay.type}{\code{Character scalar}. Specifies the name of assay +used in calculation. (Default: \code{"counts"})} -\item{niter}{The number of iterations performed. If \code{NULL}, -rarefaction is disabled. (Default: \code{NULL})} +\item{niter}{\code{Integer scalar}. Specifies the number of +rarefaction rounds. Rarefaction is not applied when \code{niter=NULL} +(see Details section). (Default: \code{NULL})} \item{transposed}{\code{Logical scalar}. Specifies if x is transposed with cells in rows. (Default: \code{FALSE})} @@ -125,10 +126,18 @@ Unifrac is calculated with \code{\link[rbiom:unifrac]{rbiom:unifrac()}}. If rarefaction is enabled, \code{\link[vegan:avgdist]{vegan:avgdist()}} is utilized. -For JSD implementation: -Susan Holmes \email{susan@stat.stanford.edu}. -Adapted for phyloseq by Paul J. McMurdie. -Adapted for mia by Felix G.M. Ernst +Rarefaction can be used to control uneven sequencing depths. Although, +it is highly debated method. Some think that it is the only option that +successfully controls the variation caused by uneven sampling depths. +The biggest argument against rarefaction is the fact that it omits data. + +Rarefaction works by sampling the counts randomly. This random sampling +is done \code{niter} times. In each sampling iteration, \code{sample} number +of random samples are drawn, and dissimilarity is calculated for this +subset. After the iterative process, there are \code{niter} number of +result that are then averaged to get the final result. + +Refer to Schloss (2024) for more details on rarefaction. } \examples{ library(mia) @@ -149,18 +158,26 @@ tse <- addDissimilarity(tse, method = "jsd") metadata(tse)[["jsd"]][1:6, 1:6] # Multi Dimensional Scaling applied to JSD dissimilarity matrix -tse <- runMDS(tse, FUN = getDissimilarity, method = "overlap", - assay.type = "counts") -metadata(tse)[["MDS"]][1:6, ] - +tse <- runMDS( + tse, FUN = getDissimilarity, method = "overlap", assay.type = "counts") +reducedDim(tse, "MDS") |> head() + ### Unifrac dissimilarity res <- getDissimilarity(tse, method = "unifrac", weighted = FALSE) -dim(as.matrix((res))) +dim(as.matrix(res)) tse <- addDissimilarity(tse, method = "unifrac", weighted = TRUE) metadata(tse)[["unifrac"]][1:6, 1:6] +### Bray dissimilarity + +# Bray is usually applied to relative abundances so we have to apply +# transformation first +tse <- transformAssay(tse, method = "relabundance") +res <- getDissimilarity(tse, method = "bray", assay.type = "relabundance") +as.matrix(res)[1:6, 1:6] + } \references{ For unifrac dissimilarity: \url{http://bmf.colorado.edu/unifrac/} @@ -183,6 +200,11 @@ Jensen-Shannon Divergence and Hilbert space embedding. Bent Fuglede and Flemming Topsoe University of Copenhagen, Department of Mathematics \url{http://www.math.ku.dk/~topsoe/ISIT2004JSD.pdf} + +For rarefaction: +Schloss PD (2024) Rarefaction is currently the best approach to control for +uneven sequencing effort in amplicon sequence analyses. \emph{mSphere} +28;9(2):e0035423. doi: 10.1128/msphere.00354-23 } \seealso{ \url{http://en.wikipedia.org/wiki/Jensen-Shannon_divergence} diff --git a/man/getDominant.Rd b/man/getDominant.Rd index 27af04f77..5b28f42ca 100644 --- a/man/getDominant.Rd +++ b/man/getDominant.Rd @@ -45,8 +45,8 @@ addDominant(x, name = "dominant_taxa", other.name = "Other", n = NULL, ...) \arguments{ \item{x}{\code{\link[TreeSummarizedExperiment:TreeSummarizedExperiment-class]{TreeSummarizedExperiment}}.} -\item{assay.type}{\code{Character scalar}. Specifies which assay to use for -calculation. (Default: \code{"counts"})} +\item{assay.type}{\code{Character scalar}. Specifies the name of assay +used in calculation. (Default: \code{"counts"})} \item{assay_name}{Deprecated. Use \code{assay.type} instead.} diff --git a/man/getPERMANOVA.Rd b/man/getPERMANOVA.Rd index 3184aa511..1d93e05b8 100644 --- a/man/getPERMANOVA.Rd +++ b/man/getPERMANOVA.Rd @@ -47,8 +47,8 @@ Options include 'permanova' (Default: \code{"permanova"}) }} -\item{assay.type}{\code{Character scalar}. Specifies which assay to use for -calculation. (Default: \code{"counts"})} +\item{assay.type}{\code{Character scalar}. Specifies the name of assay +used in calculation. (Default: \code{"counts"})} \item{formula}{\code{formula}. If \code{x} is a \code{\link[SummarizedExperiment:SummarizedExperiment-class]{SummarizedExperiment}} diff --git a/man/getPrevalence.Rd b/man/getPrevalence.Rd index 45231c87f..506cf8ca3 100644 --- a/man/getPrevalence.Rd +++ b/man/getPrevalence.Rd @@ -130,8 +130,8 @@ and \code{subsetByRare} additional parameters passed to \code{getPrevalent} }} -\item{assay.type}{\code{Character scalar}. Specifies which assay to use for -calculation. (Default: \code{"counts"})} +\item{assay.type}{\code{Character scalar}. Specifies the name of assay +used in calculation. (Default: \code{"counts"})} \item{assay_name}{Deprecated. Use \code{assay.type} instead.} diff --git a/man/isContaminant.Rd b/man/isContaminant.Rd index 7eda678cd..89bda53dc 100644 --- a/man/isContaminant.Rd +++ b/man/isContaminant.Rd @@ -60,8 +60,8 @@ passed on to \code{isContaminant}/ \code{isNotContaminant} \item{seqtab, x}{a \code{\link[SummarizedExperiment:SummarizedExperiment-class]{SummarizedExperiment}}} -\item{assay.type}{\code{Character scalar}. Specifies which assay to use for -calculation. (Default: \code{"counts"})} +\item{assay.type}{\code{Character scalar}. Specifies the name of assay +used in calculation. (Default: \code{"counts"})} \item{assay_name}{Deprecated. Use \code{assay.type} instead.} diff --git a/man/meltSE.Rd b/man/meltSE.Rd index 28aa29f5e..9c086099b 100644 --- a/man/meltSE.Rd +++ b/man/meltSE.Rd @@ -35,8 +35,8 @@ that they are syntactically valid variable names and are not duplicated. If they are not, sample names are modified. (Default: \code{TRUE}) }} -\item{assay.type}{\code{Character scalar}. Specifies which assay to use for -calculation. (Default: \code{"counts"})} +\item{assay.type}{\code{Character scalar}. Specifies the name of assay +used in calculation. (Default: \code{"counts"})} \item{assay_name}{Deprecated. Use \code{assay.type} instead.} diff --git a/man/mergeSEs.Rd b/man/mergeSEs.Rd index 90dd0cd2f..dec3e6437 100644 --- a/man/mergeSEs.Rd +++ b/man/mergeSEs.Rd @@ -33,8 +33,8 @@ mergeSEs(x, ...) \item{...}{optional arguments (not used).} -\item{assay.type}{\code{Character scalar}. Specifies which assay to use for -calculation. (Default: \code{"counts"})} +\item{assay.type}{\code{Character scalar}. Specifies the name of assay +used in calculation. (Default: \code{"counts"})} \item{assay_name}{Deprecated. Use \code{assay.type} instead.} diff --git a/man/rarefyAssay.Rd b/man/rarefyAssay.Rd index 242e5bb32..0064c7944 100644 --- a/man/rarefyAssay.Rd +++ b/man/rarefyAssay.Rd @@ -27,8 +27,8 @@ rarefyAssay(x, ...) messages. (Default: \code{TRUE}) }} -\item{assay.type}{\code{Character scalar}. Specifies which assay to use for -calculation. (Default: \code{"counts"})} +\item{assay.type}{\code{Character scalar}. Specifies the name of assay +used in calculation. (Default: \code{"counts"})} \item{assay_name}{Deprecated. Use \code{assay.type} instead.} diff --git a/man/runCCA.Rd b/man/runCCA.Rd index 4f7ae0511..77b8255cc 100644 --- a/man/runCCA.Rd +++ b/man/runCCA.Rd @@ -121,8 +121,8 @@ from \code{colData}.} of multivariate homogeneity of group dispersions be performed. (Default: \code{TRUE})} -\item{assay.type}{\code{Character scalar}. Specifies which assay to use for -calculation. (Default: \code{"counts"})} +\item{assay.type}{\code{Character scalar}. Specifies the name of assay +used in calculation. (Default: \code{"counts"})} \item{assay_name}{Deprecated. Use \code{assay.type} instead.} diff --git a/man/runDPCoA.Rd b/man/runDPCoA.Rd index e02d8159f..fb7db15fa 100644 --- a/man/runDPCoA.Rd +++ b/man/runDPCoA.Rd @@ -67,8 +67,8 @@ standardized? (Default: \code{FALSE})} \item{transposed}{\code{Logical scalar}. Specifies if x is transposed with cells in rows. (Default: \code{FALSE})} -\item{assay.type}{\code{Character scalar}. Specifies which assay to use for -calculation. (Default: \code{"counts"})} +\item{assay.type}{\code{Character scalar}. Specifies the name of assay +used in calculation. (Default: \code{"counts"})} \item{assay_name}{Deprecated. Use \code{assay.type} instead.} diff --git a/man/runNMDS.Rd b/man/runNMDS.Rd index 8c52d2200..66f2c228a 100644 --- a/man/runNMDS.Rd +++ b/man/runNMDS.Rd @@ -98,8 +98,8 @@ of the matrix returned/stored by \code{getNMDS}/ \code{addNMDS}. (Default: \item{keep_dist}{Deprecated. Use \code{keep.dist} instead.} -\item{assay.type}{\code{Character scalar}. Specifies which assay to use for -calculation. (Default: \code{"counts"})} +\item{assay.type}{\code{Character scalar}. Specifies the name of assay +used in calculation. (Default: \code{"counts"})} \item{assay_name}{Deprecated. Use \code{assay.type} instead.} diff --git a/man/transformAssay.Rd b/man/transformAssay.Rd index 5fd8e0fd0..f5b6e446a 100644 --- a/man/transformAssay.Rd +++ b/man/transformAssay.Rd @@ -53,8 +53,8 @@ If \code{NULL}, the tree is retrieved from \code{x}. (Default: \code{NULL}). }} -\item{assay.type}{\code{Character scalar}. Specifies which assay to use for -calculation. (Default: \code{"counts"})} +\item{assay.type}{\code{Character scalar}. Specifies the name of assay +used in calculation. (Default: \code{"counts"})} \item{assay_name}{Deprecated. Use \code{assay.type} instead.}