R/perform.harmony.R
In connorhknight/IBRAP: Integrated Benchmarking scRNA-seq Analytical Pipeline (IBRAP)
Defines functions
perform.harmony
Documented in
perform.harmony
#' @name perform.harmony
#' @aliases perform.harmony
#'
#' @title Performs Harmony integration
#'
#' @description Performs Harmony integration on defined method-assays and reductions contained within. This is performed on reductions.
#'
#' @param object IBRAP S4 class object
#' @param assay Character. String containing indicating which assay to use
#' @param batch Character. A string of the column nmae that contains variables to regress.
#' @param reduction Character. String defining the name of the reduction to provide for HARMONY. Default = 'pca'
#' @param reduction.save.suffix Character. What should be appended to the end of harmony as the reduction name
#' @param dims.use Numerical. Number of dimensions of the provided reduction to input into harmony, NULL equates to all dimensions. Default = NULL
#' @param print.harmony.plot Boolean. Should the automatically generated plot be printed? Default = FALSE
#' @param verbose Logical Should function messages be printed?
#' @param seed Numeric. What should the seed be set as. Default = 1234
#' @param ... Arguments to be passed to harmony::HarmonyMatrix
#'
#' @return PCA reductions contained within the computational_reduction list in the defined assays
#'
#' @examples
#'
#' object <- perform.harmony(object = object,
#' assay = c('SCRAN', 'SCT', 'SCANPY'),
#' batch = 'original.project',
#' reduction = c('pca'),
#' max.iter.harmony = 100,
#' dims.use = list(NULL))
#'
#' @export
perform.harmony <- function(object,
assay,
batch,
reduction = 'pca',
reduction.save.suffix = '',
dims.use = NULL,
print.harmony.plot = FALSE,
seed=1234,
verbose = FALSE,
...) {
if(!is(object = object, class2 = 'IBRAP')) {
stop('object must be of class IBRAP \n')
}
if(!is.character(assay)) {
stop('assay must be character string\n')
}
for(x in assay) {
if(!x %in% names(object@methods)) {
stop(paste0('reduction: ', x, 'does not exist\n'))
}
}
if(!is.character(batch)) {
stop('batch must be character string(s)\n')
}
if(!batch %in% names(object@sample_metadata)) {
stop('batch does not exist\n')
}
if(!is.character(reduction)) {
stop('reduction must be character string(s)\n')
}
for(x in reduction) {
for(i in assay) {
if(!x %in% names(c(object@methods[[i]]@computational_reductions,
object@methods[[i]]@visualisation_reductions,
object@methods[[i]]@integration_reductions))) {
stop(paste0('reduction: ', x, ' does not exist\n'))
}
}
}
if(!is.character(reduction.save.suffix)) {
stop('reduction.save.suffix must be character string(s)\n')
}
if(is.list(dims.use)) {
for(x in dims.use) {
if(!is.null(x)) {
if(!is.numeric(x)) {
stop('dims must either be numeric or NULL\n')
}
} else if (!is.numeric(x)) {
if(!is.null(x)) {
stop('dims must either be numeric or NULL\n')
}
}
}
}
if(is.null(dims.use)) {
dims.use <- list()
for(x in 1:length(reduction)) {
dims.use[[x]] <- 0
}
}
if(!is.logical(verbose)) {
stop('verbose should be logical, TRUE/FALSE \n')
}
if(!is.numeric(seed)) {
stop('seed must be a numerical value \n')
}
set.seed(seed = seed, kind = "Mersenne-Twister", normal.kind = "Inversion")
# if(!'integration_method' %in% colnames(object@pipelines)) {
#
# tmp <- tibble::add_column(.data = object@pipelines, integration_method=NA, integration_time=NA)
#
# } else {
#
# tmp <- object@pipelines
#
# }
for(p in assay) {
start_time <- Sys.time()
reduction.list <- list()
red.names <- c(names(object@methods[[p]]@computational_reductions),
names(object@methods[[p]]@integration_reductions),
names(object@methods[[p]]@visualisation_reductions))
for(i in red.names) {
if(i %in% names(object@methods[[p]]@computational_reductions)) {
reduction.list[[i]] <- object@methods[[p]]@computational_reductions[[i]]
}
if(i %in% names(object@methods[[p]]@integration_reductions)) {
reduction.list[[i]] <- object@methods[[p]]@integration_reductions[[i]]
}
if(i %in% names(object@methods[[p]]@visualisation_reductions)) {
reduction.list[[i]] <- object@methods[[p]]@visualisation_reductions[[i]]
}
}
for(r in reduction) {
if(!r %in% names(reduction.list)) {
stop('reductions could not be found\n')
}
}
count <- 1
for(g in reduction) {
red <- reduction.list[[g]]
dims <- dims.use[[count]]
if(dims == 0) {
dims <- ncol(red)
}
if('_' %in% unlist(strsplit(x = reduction.save.suffix, split = ''))) {
if(isTRUE(verbose)) {
cat(crayon::cyan(paste0(Sys.time(), ': _ cannot be used in reduction.save.suffix, replacing with - \n')))
}
reduction.save.suffix <- sub(pattern = '_', replacement = '-', x = reduction.save.suffix)
}
if(isTRUE(verbose)) {
cat(crayon::cyan(paste0(Sys.time(), ': initialising harmony for assay: ', p, ', reduction: ', g, '\n')))
}
if(isTRUE(print.harmony.plot)) {
if(isTRUE(verbose)) {
harm <- harmony::HarmonyMatrix(data_mat = red[,1:dims], meta_data = object@sample_metadata, vars_use = batch, do_pca = FALSE, verbose = TRUE, plot_convergence = TRUE, ...)
}
if(isFALSE(verbose)) {
harm <- harmony::HarmonyMatrix(data_mat = red[,1:dims], meta_data = object@sample_metadata, vars_use = batch, do_pca = FALSE, verbose = FALSE, plot_convergence = TRUE, ...)
}
}
if(isFALSE(print.harmony.plot)) {
if(isTRUE(verbose)) {
harm <- harmony::HarmonyMatrix(data_mat = red[,1:dims], meta_data = object@sample_metadata, vars_use = batch, do_pca = FALSE, verbose = TRUE, plot_convergence = FALSE, ...)
}
if(isFALSE(verbose)) {
harm <- harmony::HarmonyMatrix(data_mat = red[,1:dims], meta_data = object@sample_metadata, vars_use = batch, do_pca = FALSE, verbose = FALSE, plot_convergence = FALSE, ...)
}
}
object@methods[[p]]@integration_reductions[[paste0(r, '_HARMONY', reduction.save.suffix)]] <- harm
count <- count + 1
end_time <- Sys.time()
function_time <- end_time - start_time
# if(!'integration_method' %in% colnames(object@pipelines)) {
#
# tmp[which(x = tmp$normalisation_method==p),'integration_method'] <- paste0('HARMONY', reduction.save.suffix)
#
# tmp[which(x = tmp$normalisation_method==p),'integration_time'] <- as.difftime(function_time, units = 'secs')
#
# }
#
# if('integration_method' %in% colnames(object@pipelines)) {
#
# if(paste0('HARMONY', reduction.save.suffix) %in% tmp$integration_method) {
#
# tmp[which(tmp$normalisation_method==p & tmp$integration_method==paste0('HARMONY', reduction.save.suffix)),] <- c(tmp[which(tmp$normalisation_method==p & tmp$integration_method==paste0('HARMONY', reduction.save.suffix)),c('normalisation_method','normalisation_time')], paste0('HARMONY', reduction.save.suffix), as.difftime(function_time, units = 'secs'))
#
# }
#
# if(!paste0('HARMONY', reduction.save.suffix) %in% object@pipelines$integration_method) {
#
# df <- tmp[which(tmp$normalisation_method==p),]
#
# df <- df[!duplicated(df$normalisation_method),]
#
# df[,'integration_method'] <- paste0('HARMONY', reduction.save.suffix)
#
# df[,'integration_time'] <- function_time
#
# tmp <- rbind(tmp, df)
#
# }
#
# }
}
}
if(isTRUE(verbose)) {
cat(crayon::cyan(paste0(Sys.time(), ': harmony completed\n')))
}
# tmp$integration_time <- as.difftime(tim = tmp$integration_time, units = 'secs')
#
# rownames(tmp) <- 1:nrow(tmp)
#
# object@pipelines <- tmp
return(object)
}
connorhknight/IBRAP documentation built on March 9, 2023, 7:01 p.m.
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Defines functions perform.harmony
Documented in perform.harmony
#' @name perform.harmony
#' @aliases perform.harmony
#'
#' @title Performs Harmony integration
#'
#' @description Performs Harmony integration on defined method-assays and reductions contained within. This is performed on reductions.
#'
#' @param object IBRAP S4 class object
#' @param assay Character. String containing indicating which assay to use
#' @param batch Character. A string of the column nmae that contains variables to regress.
#' @param reduction Character. String defining the name of the reduction to provide for HARMONY. Default = 'pca'
#' @param reduction.save.suffix Character. What should be appended to the end of harmony as the reduction name
#' @param dims.use Numerical. Number of dimensions of the provided reduction to input into harmony, NULL equates to all dimensions. Default = NULL
#' @param print.harmony.plot Boolean. Should the automatically generated plot be printed? Default = FALSE
#' @param verbose Logical Should function messages be printed?
#' @param seed Numeric. What should the seed be set as. Default = 1234
#' @param ... Arguments to be passed to harmony::HarmonyMatrix
#'
#' @return PCA reductions contained within the computational_reduction list in the defined assays
#'
#' @examples
#'
#' object <- perform.harmony(object = object,
#' assay = c('SCRAN', 'SCT', 'SCANPY'),
#' batch = 'original.project',
#' reduction = c('pca'),
#' max.iter.harmony = 100,
#' dims.use = list(NULL))
#'
#' @export
perform.harmony <- function(object,
assay,
batch,
reduction = 'pca',
reduction.save.suffix = '',
dims.use = NULL,
print.harmony.plot = FALSE,
seed=1234,
verbose = FALSE,
...) {
if(!is(object = object, class2 = 'IBRAP')) {
stop('object must be of class IBRAP \n')
}
if(!is.character(assay)) {
stop('assay must be character string\n')
}
for(x in assay) {
if(!x %in% names(object@methods)) {
stop(paste0('reduction: ', x, 'does not exist\n'))
}
}
if(!is.character(batch)) {
stop('batch must be character string(s)\n')
}
if(!batch %in% names(object@sample_metadata)) {
stop('batch does not exist\n')
}
if(!is.character(reduction)) {
stop('reduction must be character string(s)\n')
}
for(x in reduction) {
for(i in assay) {
if(!x %in% names(c(object@methods[[i]]@computational_reductions,
object@methods[[i]]@visualisation_reductions,
object@methods[[i]]@integration_reductions))) {
stop(paste0('reduction: ', x, ' does not exist\n'))
}
}
}
if(!is.character(reduction.save.suffix)) {
stop('reduction.save.suffix must be character string(s)\n')
}
if(is.list(dims.use)) {
for(x in dims.use) {
if(!is.null(x)) {
if(!is.numeric(x)) {
stop('dims must either be numeric or NULL\n')
}
} else if (!is.numeric(x)) {
if(!is.null(x)) {
stop('dims must either be numeric or NULL\n')
}
}
}
}
if(is.null(dims.use)) {
dims.use <- list()
for(x in 1:length(reduction)) {
dims.use[[x]] <- 0
}
}
if(!is.logical(verbose)) {
stop('verbose should be logical, TRUE/FALSE \n')
}
if(!is.numeric(seed)) {
stop('seed must be a numerical value \n')
}
set.seed(seed = seed, kind = "Mersenne-Twister", normal.kind = "Inversion")
# if(!'integration_method' %in% colnames(object@pipelines)) {
#
# tmp <- tibble::add_column(.data = object@pipelines, integration_method=NA, integration_time=NA)
#
# } else {
#
# tmp <- object@pipelines
#
# }
for(p in assay) {
start_time <- Sys.time()
reduction.list <- list()
red.names <- c(names(object@methods[[p]]@computational_reductions),
names(object@methods[[p]]@integration_reductions),
names(object@methods[[p]]@visualisation_reductions))
for(i in red.names) {
if(i %in% names(object@methods[[p]]@computational_reductions)) {
reduction.list[[i]] <- object@methods[[p]]@computational_reductions[[i]]
}
if(i %in% names(object@methods[[p]]@integration_reductions)) {
reduction.list[[i]] <- object@methods[[p]]@integration_reductions[[i]]
}
if(i %in% names(object@methods[[p]]@visualisation_reductions)) {
reduction.list[[i]] <- object@methods[[p]]@visualisation_reductions[[i]]
}
}
for(r in reduction) {
if(!r %in% names(reduction.list)) {
stop('reductions could not be found\n')
}
}
count <- 1
for(g in reduction) {
red <- reduction.list[[g]]
dims <- dims.use[[count]]
if(dims == 0) {
dims <- ncol(red)
}
if('_' %in% unlist(strsplit(x = reduction.save.suffix, split = ''))) {
if(isTRUE(verbose)) {
cat(crayon::cyan(paste0(Sys.time(), ': _ cannot be used in reduction.save.suffix, replacing with - \n')))
}
reduction.save.suffix <- sub(pattern = '_', replacement = '-', x = reduction.save.suffix)
}
if(isTRUE(verbose)) {
cat(crayon::cyan(paste0(Sys.time(), ': initialising harmony for assay: ', p, ', reduction: ', g, '\n')))
}
if(isTRUE(print.harmony.plot)) {
if(isTRUE(verbose)) {
harm <- harmony::HarmonyMatrix(data_mat = red[,1:dims], meta_data = object@sample_metadata, vars_use = batch, do_pca = FALSE, verbose = TRUE, plot_convergence = TRUE, ...)
}
if(isFALSE(verbose)) {
harm <- harmony::HarmonyMatrix(data_mat = red[,1:dims], meta_data = object@sample_metadata, vars_use = batch, do_pca = FALSE, verbose = FALSE, plot_convergence = TRUE, ...)
}
}
if(isFALSE(print.harmony.plot)) {
if(isTRUE(verbose)) {
harm <- harmony::HarmonyMatrix(data_mat = red[,1:dims], meta_data = object@sample_metadata, vars_use = batch, do_pca = FALSE, verbose = TRUE, plot_convergence = FALSE, ...)
}
if(isFALSE(verbose)) {
harm <- harmony::HarmonyMatrix(data_mat = red[,1:dims], meta_data = object@sample_metadata, vars_use = batch, do_pca = FALSE, verbose = FALSE, plot_convergence = FALSE, ...)
}
}
object@methods[[p]]@integration_reductions[[paste0(r, '_HARMONY', reduction.save.suffix)]] <- harm
count <- count + 1
end_time <- Sys.time()
function_time <- end_time - start_time
# if(!'integration_method' %in% colnames(object@pipelines)) {
#
# tmp[which(x = tmp$normalisation_method==p),'integration_method'] <- paste0('HARMONY', reduction.save.suffix)
#
# tmp[which(x = tmp$normalisation_method==p),'integration_time'] <- as.difftime(function_time, units = 'secs')
#
# }
#
# if('integration_method' %in% colnames(object@pipelines)) {
#
# if(paste0('HARMONY', reduction.save.suffix) %in% tmp$integration_method) {
#
# tmp[which(tmp$normalisation_method==p & tmp$integration_method==paste0('HARMONY', reduction.save.suffix)),] <- c(tmp[which(tmp$normalisation_method==p & tmp$integration_method==paste0('HARMONY', reduction.save.suffix)),c('normalisation_method','normalisation_time')], paste0('HARMONY', reduction.save.suffix), as.difftime(function_time, units = 'secs'))
#
# }
#
# if(!paste0('HARMONY', reduction.save.suffix) %in% object@pipelines$integration_method) {
#
# df <- tmp[which(tmp$normalisation_method==p),]
#
# df <- df[!duplicated(df$normalisation_method),]
#
# df[,'integration_method'] <- paste0('HARMONY', reduction.save.suffix)
#
# df[,'integration_time'] <- function_time
#
# tmp <- rbind(tmp, df)
#
# }
#
# }
}
}
if(isTRUE(verbose)) {
cat(crayon::cyan(paste0(Sys.time(), ': harmony completed\n')))
}
# tmp$integration_time <- as.difftime(tim = tmp$integration_time, units = 'secs')
#
# rownames(tmp) <- 1:nrow(tmp)
#
# object@pipelines <- tmp
return(object)
}
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