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SCP-app.R
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#' CreateDataFile
#'
#' @param srt
#'
#' @param DataFile
#' @param name
#' @param assays
#' @param slots
#' @param compression_level
#' @param overwrite
#'
#' @importFrom Seurat GetAssayData
#' @importFrom SeuratObject as.sparse
#' @export
CreateDataFile <- function(srt, DataFile, name = NULL, assays = "RNA", slots = "data", compression_level = 6, overwrite = FALSE) {
check_R("HDF5Array")
if (missing(DataFile) || is.null(DataFile)) {
DataFile <- "Data.hdf5"
}
if (!file.exists(DataFile)) {
rhdf5::h5createFile(DataFile)
}
if (is.null(name)) {
name <- [email protected]
message("Set the dataset name to ", name)
}
if (substr(name, 1, 1) != "/") {
name <- paste0("/", name)
}
if (!name %in% rhdf5::h5ls(DataFile)$group) {
rhdf5::h5createGroup(file = DataFile, group = name)
}
message("Write the expression matrix to hdf5 file: ", DataFile)
for (assay in assays) {
for (slot in slots) {
data <- t(GetAssayData(srt, slot = slot, assay = assay))
if (isTRUE(overwrite)) {
try(rhdf5::h5delete(file = DataFile, name = paste0(name, "/", assay, "/", slot)), silent = TRUE)
}
if (paste0(name, "/", assay, "/", slot) %in% rhdf5::h5ls(DataFile)$group) {
message("Group ", paste0(name, "/", assay, "/", slot), " already exists in the ", DataFile)
} else {
if (!paste0(name, "/", assay) %in% rhdf5::h5ls(DataFile)$group) {
rhdf5::h5createGroup(file = DataFile, group = paste0(name, "/", assay))
}
if (!inherits(data, "dgCMatrix")) {
data <- as.sparse(data[1:nrow(data), ])
}
HDF5Array::writeTENxMatrix(x = data, filepath = DataFile, group = paste0(name, "/", assay, "/", slot), level = compression_level)
}
}
}
if (isTRUE(overwrite)) {
try(rhdf5::h5delete(file = DataFile, name = paste0(name, "/Default_assay")), silent = TRUE)
}
if (paste0(name, "/Default_assay") %in% rhdf5::h5ls(DataFile)$group) {
message("Group ", paste0(name, "/Default_assay"), " already exists in the ", DataFile)
} else {
rhdf5::h5write(obj = DefaultAssay(srt), file = DataFile, name = paste0(name, "/Default_assay"), level = compression_level)
}
if (isTRUE(overwrite)) {
try(rhdf5::h5delete(file = DataFile, name = paste0(name, "/cells")), silent = TRUE)
}
if (paste0(name, "/cells") %in% rhdf5::h5ls(DataFile)$group) {
message("Group ", paste0(name, "/cells"), " already exists in the ", DataFile)
} else {
rhdf5::h5write(obj = colnames(srt), file = DataFile, name = paste0(name, "/cells"), level = compression_level)
}
if (isTRUE(overwrite)) {
try(rhdf5::h5delete(file = DataFile, name = paste0(name, "/features")), silent = TRUE)
}
if (paste0(name, "/features") %in% rhdf5::h5ls(DataFile)$group) {
message("Group ", paste0(name, "/features"), " already exists in the ", DataFile)
} else {
rhdf5::h5write(obj = unique(unlist(lapply(srt@assays, rownames))), file = DataFile, name = paste0(name, "/features"), level = compression_level)
}
return(invisible(NULL))
}
#' CreateMetaFile
#'
#' @param srt
#'
#' @param MetaFile
#' @param name
#' @param write_tools
#' @param write_misc
#' @param ignore_nlevel
#' @param compression_level
#' @param overwrite
#'
#' @importFrom Seurat Key Reductions Embeddings
#' @importFrom Matrix sparseMatrix
#' @export
CreateMetaFile <- function(srt, MetaFile, name = NULL, write_tools = FALSE, write_misc = FALSE, ignore_nlevel = 100, compression_level = 6, overwrite = FALSE) {
if (missing(MetaFile) || is.null(MetaFile)) {
MetaFile <- "Meta.hdf5"
}
if (!file.exists(MetaFile)) {
rhdf5::h5createFile(MetaFile)
}
if (is.null(name)) {
name <- [email protected]
message("Set the dataset name to ", name)
}
if (substr(name, 1, 1) != "/") {
name <- paste0("/", name)
}
if (!name %in% rhdf5::h5ls(MetaFile)$group) {
rhdf5::h5createGroup(file = MetaFile, group = name)
}
message("Write the meta information to hdf5 file: ", MetaFile)
if (!paste0(name, "/metadata") %in% rhdf5::h5ls(MetaFile)$group) {
rhdf5::h5createGroup(file = MetaFile, group = paste0(name, "/metadata"))
}
meta_asfeatures <- c()
meta_asgroups <- c()
for (var in colnames(srt[[]])) {
meta <- srt[[var, drop = TRUE]][colnames(srt)]
if (inherits(meta, "factor")) {
levels <- levels(meta)
meta <- as.character(meta)
attr(meta, "levels") <- levels
write.attributes <- TRUE
} else if (inherits(meta, "logical")) {
levels <- c("TRUE", "FALSE")
meta <- as.character(meta)
attr(meta, "levels") <- levels
write.attributes <- TRUE
} else {
write.attributes <- FALSE
}
if (inherits(meta, "numeric")) {
meta <- as.double(meta)
meta_asfeatures <- c(meta_asfeatures, var)
}
if (!is.numeric(meta)) {
if (length(unique(meta)) > ignore_nlevel) {
warning("The number of categories in ", var, " is greater than ", ignore_nlevel, ", it will be ignored.", immediate. = TRUE)
} else {
meta_asgroups <- c(meta_asgroups, var)
}
}
if (isTRUE(overwrite)) {
try(rhdf5::h5delete(file = MetaFile, name = paste0(name, "/metadata/", var)), silent = TRUE)
}
if (paste0(name, "/metadata/", var) %in% paste0(rhdf5::h5ls(MetaFile)$group, "/", rhdf5::h5ls(MetaFile)$name)) {
message("Group ", paste0(name, "/metadata/", var), " already exists in the ", MetaFile)
} else {
rhdf5::h5write(obj = meta, file = MetaFile, name = paste0(name, "/metadata/", var), write.attributes = write.attributes, level = compression_level)
}
}
if (isTRUE(overwrite)) {
try(rhdf5::h5delete(file = MetaFile, name = paste0(name, "/metadata.stat")), silent = TRUE)
}
if (paste0(name, "/metadata.stat") %in% rhdf5::h5ls(MetaFile)$group) {
message("Group ", paste0(name, "/metadata.stat"), " already exists in the ", MetaFile)
} else {
rhdf5::h5createGroup(file = MetaFile, group = paste0(name, "/metadata.stat"))
rhdf5::h5write(obj = meta_asfeatures, file = MetaFile, name = paste0(name, "/metadata.stat/asfeatures"), level = compression_level)
rhdf5::h5write(obj = meta_asgroups, file = MetaFile, name = paste0(name, "/metadata.stat/asgroups"), level = compression_level)
}
if (!paste0(name, "/reductions") %in% rhdf5::h5ls(MetaFile)$group) {
rhdf5::h5createGroup(file = MetaFile, group = paste0(name, "/reductions"))
}
for (reduction in Reductions(srt)) {
emb <- Embeddings(srt, reduction)[colnames(srt), ]
attr(emb, "key") <- as.character(Key(srt[[reduction]]))
if (isTRUE(overwrite)) {
try(rhdf5::h5delete(file = MetaFile, name = paste0(name, "/reductions/", reduction)), silent = TRUE)
}
if (paste0(name, "/reductions/", reduction) %in% paste0(rhdf5::h5ls(MetaFile)$group, "/", rhdf5::h5ls(MetaFile)$name)) {
message("Group ", paste0(name, "/reductions/", reduction), " already exists in the ", MetaFile)
} else {
rhdf5::h5createDataset(
file = MetaFile, dataset = paste0(name, "/reductions/", reduction),
dims = dim(emb), chunk = c(nrow(emb), min(10, ncol(emb))), level = compression_level
)
suppressWarnings(rhdf5::h5write(obj = emb, file = MetaFile, name = paste0(name, "/reductions/", reduction), write.attributes = TRUE, level = compression_level))
}
}
if (isTRUE(overwrite)) {
try(rhdf5::h5delete(file = MetaFile, name = paste0(name, "/reductions.stat")), silent = TRUE)
}
if (paste0(name, "/reductions.stat") %in% rhdf5::h5ls(MetaFile)$group) {
message("Group ", paste0(name, "/reductions.stat"), " already exists in the ", MetaFile)
} else {
rhdf5::h5createGroup(file = MetaFile, group = paste0(name, "/reductions.stat"))
rhdf5::h5write(obj = DefaultReduction(srt), file = MetaFile, name = paste0(name, "/reductions.stat/Default_reduction"), level = compression_level)
}
if (isTRUE(write_misc)) {
if (isTRUE(overwrite)) {
try(rhdf5::h5delete(file = MetaFile, name = paste0(name, "/misc")), silent = TRUE)
}
if (paste0(name, "/misc") %in% rhdf5::h5ls(MetaFile)$group) {
message("Group ", paste0(name, "/misc"), " already exists in the ", MetaFile)
} else {
rhdf5::h5write(obj = srt@misc, file = MetaFile, name = paste0(name, "/misc"), level = compression_level)
}
}
if (isTRUE(write_tools)) {
if (isTRUE(overwrite)) {
try(rhdf5::h5delete(file = MetaFile, name = paste0(name, "/tools")), silent = TRUE)
}
if (paste0(name, "/tools") %in% rhdf5::h5ls(MetaFile)$group) {
message("Group ", paste0(name, "/tools"), " already exists in the ", MetaFile)
} else {
rhdf5::h5write(obj = srt@tools, file = MetaFile, name = paste0(name, "/tools"), level = compression_level)
}
}
return(invisible(NULL))
}
#' Prepare Seurat object data for the SCExplorer into hdf5 file
#'
#' @param object
#' @param base_dir
#' @param DataFile
#' @param MetaFile
#' @param assays
#' @param slots
#' @param ignore_nlevel
#' @param write_tools
#' @param write_misc
#' @param compression_level
#' @param overwrite
#'
#' @examples
#' \dontrun{
#' data("pancreas_sub")
#' pancreas_sub <- Standard_SCP(pancreas_sub)
#' PrepareSCExplorer(pancreas_sub, base_dir = "./SCExplorer")
#' }
#' @importFrom Seurat Reductions Assays DefaultAssay
#' @export
PrepareSCExplorer <- function(object,
base_dir = "SCExplorer", DataFile = "Data.hdf5", MetaFile = "Meta.hdf5",
assays = "RNA", slots = c("counts", "data"),
ignore_nlevel = 100, write_tools = FALSE, write_misc = FALSE,
compression_level = 6, overwrite = FALSE) {
base_dir <- R.utils::getAbsolutePath(base_dir)
if (!dir.exists(base_dir)) {
message("Create SCExplorer base directory: ", base_dir)
dir.create(base_dir, recursive = TRUE, showWarnings = FALSE)
}
DataFile_full <- paste0(base_dir, "/", DataFile)
MetaFile_full <- paste0(base_dir, "/", MetaFile)
if (!is.list(object)) {
object <- list(object)
}
if (any(sapply(object, function(x) !inherits(x, "Seurat")))) {
stop("'object' must be one Seurat object or a list of Seurat object.")
}
if (length(names(object)) > 0 && length(names(object)) != length(object)) {
stop("The object is named, but the name length is not equal to the number of elements.")
}
if (length(names(object)) == 0) {
names(object) <- make.names(sapply(object, function(x) [email protected]), unique = TRUE)
message("Set the project name of each seurat object to their dataset name")
}
for (i in seq_along(object)) {
nm <- names(object)[i]
srt <- object[[nm]]
message("Prepare data for object: ", nm)
if (length(Reductions(srt)) == 0) {
stop("No reduction found in the Seurat object ", i)
}
if (!any(assays %in% Assays(srt))) {
warning("Assay:", assays[!assays %in% Assays(srt)], " is not in the Seurat object ", i, immediate. = TRUE)
assays <- assays[assays %in% Assays(srt)]
if (length(assays) == 0) {
warning("No assays found in the Seurat object ", i, ". Use the default assay to create data file.")
assays <- DefaultAssay(srt)
}
}
if (!"orig.ident" %in% colnames(srt[[]])) {
srt[["orig.ident"]] <- "SeuratObject"
}
CreateDataFile(
srt = srt, DataFile = DataFile_full, name = nm, assays = assays, slots = slots,
compression_level = compression_level, overwrite = overwrite
)
CreateMetaFile(
srt = srt, MetaFile = MetaFile_full, name = nm, ignore_nlevel = ignore_nlevel,
write_tools = write_tools, write_misc = write_misc,
compression_level = compression_level, overwrite = overwrite
)
}
return(invisible(NULL))
}
#' Fetch data from the hdf5 file
#'
#' @param DataFile
#' @param MetaFile
#' @param name
#' @param features
#' @param slot
#' @param assay
#' @param metanames
#' @param reduction
#'
#' @examples
#' \dontrun{
#' data("pancreas_sub")
#' pancreas_sub <- Standard_SCP(pancreas_sub)
#' PrepareSCExplorer(pancreas_sub, base_dir = "./SCExplorer")
#' srt <- FetchH5(DataFile = "./SCExplorer/Data.hdf5", MetaFile = "./SCExplorer/Meta.hdf5", features = c("Ins1", "Ghrl"), metanames = c("SubCellType", "Phase"), reduction = "UMAP")
#' ClassDimPlot(srt, group.by = c("SubCellType", "Phase"), reduction = "UMAP")
#' ExpDimPlot(srt, features = c("Ins1", "Ghrl"), reduction = "UMAP")
#' }
#' @importFrom Seurat CreateSeuratObject CreateDimReducObject
#' @importFrom Matrix sparseMatrix
#' @importFrom rlang %||%
#' @export
FetchH5 <- function(DataFile, MetaFile, name = NULL,
features = NULL, slot = NULL, assay = NULL,
metanames = NULL,
reduction = NULL) {
check_R(c("HDF5Array", "rhdf5"))
if (missing(DataFile) || missing(MetaFile)) {
stop("'DataFile', 'MetaFile' must be provided.")
}
data_group <- rhdf5::h5ls(DataFile)$group
meta_group <- rhdf5::h5ls(MetaFile)$group
if (is.null(name)) {
group <- intersect(data_group, meta_group)
group <- group[group != "/"]
group <- sapply(group, function(x) substr(x, 2, nchar(x)))
if (length(group) == 0) {
stop("Can not find the shared group name in the DataFile and the MetaFile. They may not correspond to the same project.")
} else if (length(group) > 1) {
message(length(group), " possible dataset names were found: ", paste(group, collapse = ", "), "\nUse the first one.")
}
name <- group[1]
}
if (substr(name, 1, 1) != "/") {
name <- paste0("/", name)
}
all_features <- rhdf5::h5read(DataFile, name = paste0(name, "/features"))
all_cells <- rhdf5::h5read(DataFile, name = paste0(name, "/cells"))
meta_struc <- rhdf5::h5ls(MetaFile)
meta_features_name <- rhdf5::h5read(MetaFile, name = paste0(name, "/metadata.stat/asfeatures"))
meta_groups_name <- rhdf5::h5read(MetaFile, name = paste0(name, "/metadata.stat/asgroups"))
reduction_name <- meta_struc[meta_struc$group == paste0(name, "/reductions"), "name"]
if (!is.null(features) && any(!features %in% c(all_features, meta_features_name))) {
warning("Can not find the features: ", paste0(features[!features %in% c(all_features, meta_features_name)], collapse = ","), immediate. = TRUE)
}
gene_features <- features[features %in% c(all_features)]
meta_features <- features[features %in% c(meta_features_name)]
if (!is.null(metanames) && any(!metanames %in% c(meta_features_name, meta_groups_name))) {
warning("Can not find the meta information: ", paste0(metanames[!metanames %in% c(meta_features_name, meta_groups_name)], collapse = ","), immediate. = TRUE)
}
metanames <- metanames[metanames %in% c(meta_features_name, meta_groups_name)]
if (length(gene_features) == 0 && length(meta_features) == 0 && length(metanames) == 0) {
stop("No features or meta information found.")
}
if (length(gene_features) > 0) {
if (is.null(assay)) {
assay <- as.character(rhdf5::h5read(DataFile, name = paste0(name, "/Default_assay")))
}
if (is.null(slot)) {
slots <- as.character(unique(na.omit(sapply(strsplit(data_group[grep(name, data_group)], "/"), function(x) x[4]))))
slot <- ifelse("data" %in% slots, "data", slots[1])
}
if (!paste0(name, "/", assay, "/", slot) %in% rhdf5::h5ls(DataFile)[["group"]]) {
stop("There is no ", paste0(name, "/", assay, "/", slot), " in DataFile, please write it first using the PrepareSCExplorer function")
}
data <- HDF5Array::TENxMatrix(filepath = DataFile, group = paste0(name, "/", assay, "/", slot))
gene_features <- gene_features[gene_features %in% colnames(data)]
}
if (length(gene_features) > 0) {
srt_tmp <- CreateSeuratObject(assay = assay %||% "RNA", counts = as(t(data[, gene_features, drop = FALSE]), "matrix")) # sparseMatrix
} else {
srt_tmp <- CreateSeuratObject(assay = assay %||% "RNA", counts = matrix(data = 0, ncol = length(all_cells), dimnames = list("empty", all_cells)))
}
if (length(c(metanames, meta_features)) > 0) {
for (i in unique(c(metanames, meta_features))) {
meta <- rhdf5::h5read(MetaFile, name = paste0(name, "/metadata/", i))
if (is.array(meta)) {
if (is.integer(meta)) {
meta <- as.integer(meta)
} else if (is.numeric(meta)) {
meta <- as.numeric(meta)
} else if (is.character(meta)) {
meta <- as.character(meta)
}
}
meta_attr <- rhdf5::h5readAttributes(MetaFile, name = paste0(name, "/metadata/", i))
if ("levels" %in% names(meta_attr)) {
meta <- factor(meta, levels = meta_attr$levels)
}
[email protected][, i] <- meta
}
}
if (!is.null(reduction)) {
reduction <- reduction_name[agrep(reduction, reduction_name)]
if (length(reduction) == 0) {
stop("Can not find the reduction: ", as.character(reduction))
}
for (i in reduction) {
reduction <- as.matrix(rhdf5::h5read(MetaFile, name = paste0(name, "/reductions/", i)))
reduction_attr <- rhdf5::h5readAttributes(MetaFile, name = paste0(name, "/reductions/", i))
rownames(reduction) <- all_cells
colnames(reduction) <- paste0(as.character(reduction_attr$key), seq_len(ncol(reduction)))
srt_tmp@reductions[[i]] <- CreateDimReducObject(
embeddings = reduction,
key = as.character(reduction_attr$key),
assay = assay %||% DefaultAssay(srt_tmp)
)
}
}
return(srt_tmp)
}
#' RunSCExplorer
#'
#' @param base_dir
#' @param DataFile
#' @param MetaFile
#' @param title
#' @param initial_dataset
#' @param initial_reduction
#' @param initial_group
#' @param initial_feature
#' @param initial_assay
#' @param initial_slot
#' @param initial_label
#' @param initial_palette1
#' @param initial_palette2
#' @param initial_theme1
#' @param initial_theme2
#' @param initial_coExp
#' @param initial_size
#' @param initial_ncol
#' @param initial_arrange
#' @param initial_panel_dpi
#' @param initial_dpi
#' @param create_script
#' @param style_script
#' @param overwrite
#' @param return_app
#'
#' @examples
#' \dontrun{
#' data("pancreas_sub")
#' pancreas_sub <- Standard_SCP(pancreas_sub)
#' data("panc8_sub")
#' panc8_sub <- Integration_SCP(srtMerge = panc8_sub, batch = "tech", integration_method = "Seurat")
#'
#' PrepareSCExplorer(list(mouse_pancreas = pancreas_sub, human_pancreas = panc8_sub), base_dir = "./SCExplorer", overwrite = TRUE)
#'
#' # Create the app.R script
#' app <- RunSCExplorer(base_dir = "./SCExplorer", overwrite = TRUE)
#' list.files("./SCExplorer") # This directory can be used as site directory for Shiny Server.
#'
#' # Run shiny app
#' if (interactive()) {
#' shiny::runApp(app)
#' }
#' # Note: If SCP installed in the isolated environment using renv, you need to add `renv::activate(project = "path/to/SCP_env")` to the app.R script.
#'
#' ####################################################################################################################
#' # You can deploy the app on the self-hosted shiny server(https://www.rstudio.com/products/shiny/shiny-server/).
#' # Or deploy the app on the website(https://www.shinyapps.io) for free:
#'
#' ### step1: set the repository URL for Bioconductor packages and update them to the latest version
#' # options(repos = BiocManager::repositories())
#' # BiocManager::install(ask = FALSE)
#'
#' ### step2: install "rsconnect" package and authorize your account
#' # install.packages("rsconnect")
#' # library(rsconnect)
#' # setAccountInfo(name = "<NAME>", token = "<TOKEN>", secret = "<SECRET>")
#'
#' ### step3: deploy the app
#' # deployApp("./SCExplorer")
#' }
#'
#' @importFrom rlang %||%
#' @export
RunSCExplorer <- function(base_dir = "SCExplorer",
DataFile = "Data.hdf5",
MetaFile = "Meta.hdf5",
title = "SCExplorer",
initial_dataset = NULL,
initial_reduction = NULL,
initial_group = NULL,
initial_feature = NULL,
initial_assay = NULL,
initial_slot = NULL,
initial_label = "No",
initial_palette1 = "Paired",
initial_palette2 = "Spectral",
initial_theme1 = "theme_scp",
initial_theme2 = "theme_scp",
initial_coExp = "No",
initial_size = 4,
initial_ncol = 3,
initial_arrange = "Row",
initial_dpi = 100,
initial_raster = FALSE,
create_script = TRUE,
style_script = require("styler", quietly = TRUE),
overwrite = FALSE,
return_app = TRUE) {
check_R(c("shiny", "shinycssloaders"))
DataFile_full <- paste0(base_dir, "/", DataFile)
MetaFile_full <- paste0(base_dir, "/", MetaFile)
if (!file.exists(DataFile_full) || !file.exists(MetaFile_full)) {
stop("Please create the DataFile and MetaFile using PrepareSCExplorer function first!")
}
main_code <- '
data_group <- rhdf5::h5ls(DataFile)$group
meta_group <- rhdf5::h5ls(MetaFile)$group
group <- intersect(data_group, meta_group)
group <- group[group != "/"]
group <- as.character(sapply(group, function(x) substr(x, 2, nchar(x))))
if (length(group) == 0) {
stop("Can not find the shared group names in the DataFile and the MetaFile. They may not correspond to the same project.")
}
if (is.null(initial_dataset)) {
initial_dataset <- group[1]
}
if (substr(initial_dataset, 1, 1) == "/") {
initial_dataset <- substr(initial_dataset, 2, nchar(initial_dataset))
}
if (!initial_dataset %in% group) {
stop("Dataset ", group, " is not in the DataFile and the MetaFile")
}
assays <- unique(na.omit(sapply(strsplit(data_group[grep(initial_dataset, data_group)], "/"), function(x) x[3])))
slots <- unique(na.omit(sapply(strsplit(data_group[grep(initial_dataset, data_group)], "/"), function(x) x[4])))
if (is.null(initial_assay)) {
initial_assay <- as.character(rhdf5::h5read(DataFile, name = paste0("/", initial_dataset, "/Default_assay")))
}
if (is.null(initial_slot)) {
initial_slot <- ifelse("data" %in% slots, "data", slots[1])
}
if (!initial_assay %in% assays) {
stop("initial_assay is not in the dataset ", initial_dataset, " in the DataFile")
}
if (!initial_slot %in% slots) {
stop("initial_slot is not in the dataset ", initial_slot, " in the DataFile")
}
data <- HDF5Array::TENxMatrix(filepath = DataFile, group = paste0("/", initial_dataset, "/", initial_assay, "/", initial_slot))
all_features <- colnames(data)
meta_struc <- rhdf5::h5ls(MetaFile)
meta_features_name <- rhdf5::h5read(MetaFile, name = paste0("/", initial_dataset, "/metadata.stat/asfeatures"))
meta_groups_name <- rhdf5::h5read(MetaFile, name = paste0("/", initial_dataset, "/metadata.stat/asgroups"))
reduction_name <- meta_struc[meta_struc$group == paste0("/", initial_dataset, "/reductions"), "name"]
default_reduction <- as.character(rhdf5::h5read(MetaFile, name = paste0("/", initial_dataset, "/reductions.stat/Default_reduction")))
if (is.null(initial_reduction)) {
initial_reduction <- default_reduction
}
if (is.null(initial_group)) {
initial_group <- "orig.ident"
}
if (is.null(initial_feature)) {
initial_feature <- meta_features_name[1]
}
initial_srt_tmp <- SCP::FetchH5(
DataFile = DataFile, MetaFile = MetaFile, name = initial_dataset,
features = initial_feature, slot = initial_slot, assay = initial_assay,
metanames = initial_group, reduction = initial_reduction
)
initial_p1_dim <- SCP::ClassDimPlot(
srt = initial_srt_tmp, group.by = initial_group, reduction = initial_reduction, raster = initial_raster,
label = ifelse(initial_label == "Yes", TRUE, FALSE), palette = initial_palette1, theme_use = initial_theme1,
ncol = initial_ncol, byrow = ifelse(initial_arrange == "Row", TRUE, FALSE), force = TRUE
)
initial_p1_dim <- SCP::panel_fix(initial_p1_dim, height = initial_size, raster = FALSE, verbose = FALSE)
initial_p2_dim <- SCP::ExpDimPlot(
srt = initial_srt_tmp, features = initial_feature, reduction = initial_reduction, slot = "data", raster = initial_raster,
calculate_coexp = ifelse(initial_coExp == "Yes", TRUE, FALSE), palette = initial_palette2, theme_use = initial_theme2,
ncol = initial_ncol, byrow = ifelse(initial_arrange == "Row", TRUE, FALSE)
)
initial_p2_dim <- SCP::panel_fix(initial_p2_dim, height = initial_size, raster = FALSE, verbose = FALSE)
initial_p2_vln <- SCP::ExpStatPlot(
srt = initial_srt_tmp, features = initial_feature, group.by = initial_group,
calculate_coexp = ifelse(initial_coExp == "Yes", TRUE, FALSE), palette = initial_palette2,
ncol = initial_ncol, byrow = ifelse(initial_arrange == "Row", TRUE, FALSE), force = TRUE
)
initial_p2_vln <- SCP::panel_fix(initial_p2_vln, height = initial_size, raster = FALSE, verbose = FALSE)
initial_plot3d <- max(sapply(names(initial_srt_tmp@reductions), function(r) dim(initial_srt_tmp[[r]])[2])) >= 3
if (isTRUE(initial_plot3d)) {
initial_p1_3d <- SCP::ClassDimPlot3D(
srt = initial_srt_tmp, group.by = initial_group, reduction = initial_reduction, palette = initial_palette1,
force = TRUE
)
initial_p2_3d <- SCP::ExpDimPlot3D(
srt = initial_srt_tmp, features = initial_feature, reduction = initial_reduction,
calculate_coexp = ifelse(initial_coExp == "Yes", TRUE, FALSE)
)
} else {
initial_p1_3d <- initial_p2_3d <- NULL
}
palette_list <- SCP:::palette_list
# ui ----------------------------------------------------------------------
ui <- fluidPage(
navbarPage(
title = title,
tabPanel(
"Cell classification view",
sidebarPanel(
width = 3,
selectInput(
inputId = "dataset1",
label = "Select a dataset",
choices = group,
selected = substr(initial_dataset, 2, nchar(initial_dataset))
),
selectInput(
inputId = "reduction1",
label = "Select a reduction",
choices = reduction_name,
selected = initial_reduction
),
selectInput(
inputId = "class1",
label = "Select a categorical variable",
choices = meta_groups_name,
selected = initial_group
),
selectInput(
inputId = "split1",
label = "Select a variable for splitting",
choices = c("None", meta_groups_name),
selected = "None"
),
radioButtons(
inputId = "label1",
label = "Whether labeled",
choices = c("Yes", "No"),
selected = initial_label,
inline = TRUE
),
selectInput(
inputId = "palette1",
label = "Select a palette",
choices = names(palette_list),
selected = initial_palette1
),
selectInput(
inputId = "theme1",
label = "Select a theme",
choices = c("theme_scp", "theme_blank"),
selected = initial_theme1
),
selectInput(
inputId = "raster1",
label = "Raster",
choices = c("TRUE", "FALSE"),
selected = initial_raster
),
numericInput(
inputId = "size1",
label = "Panel size",
value = initial_size,
min = 1,
max = 10,
step = 0.1,
width = "150px"
),
numericInput(
inputId = "plot_dpi1",
label = "Resolution of the plot",
value = initial_dpi,
min = 50,
max = 1000,
step = 50,
width = "150px"
),
numericInput(
inputId = "ncol1",
label = "Number of columns",
value = initial_ncol,
min = 1,
max = 100,
step = 1,
width = "150px"
),
radioButtons(
inputId = "arrange1",
label = "Arrange by",
choices = c("Row", "Column"),
selected = initial_arrange,
inline = TRUE
),
actionButton(inputId = "submit1", label = "Submit", icon("play")),
helpText("Click the submit button to update the plot displayed in the right panel.")
),
mainPanel(
width = 9,
fluidPage(
tabsetPanel(
tabPanel(
title = "2D plot",
column(
width = 12, offset = 0, style = "padding:0px;margin:0%",
div(
style = "overflow-x: auto;",
shinycssloaders::withSpinner(plotOutput("plot1", height = "100%", width = "100%"))
)
)
),
tabPanel(
title = "3D plot",
column(
width = 12, offset = 0, style = "padding:0px;margin:0%",
div(
style = "overflow-x: auto;",
shinycssloaders::withSpinner(plotly::plotlyOutput("plot1_3d", height = "100%", width = "100%"))
)
)
)
)
)
)
),
tabPanel(
"Feature expression view",
sidebarPanel(
width = 3,
selectInput(
inputId = "dataset2",
label = "Select a dataset",
choices = group,
selected = substr(initial_dataset, 2, nchar(initial_dataset))
),
selectInput(
inputId = "reduction2",
label = "Select a reduction",
choices = reduction_name,
selected = initial_reduction
),
selectInput(
inputId = "assays2",
label = "Select a assay",
choices = assays,
selected = initial_assay
),
selectInput(
inputId = "slots2",
label = "Select a slot",
choices = slots,
selected = initial_slot
),
selectizeInput(
inputId = "features2",
label = "Select genes",
choices = NULL,
selected = initial_feature,
multiple = TRUE,
options = list(maxOptions = 20, maxItems = 20)
),
textAreaInput(
inputId = "gene_area",
label = "Input genes",
height = "200px",
placeholder = paste(sample(all_features, 4), collapse = "\n")
),
selectInput(
inputId = "split2",
label = "Select a variable for splitting",
choices = c("None", meta_groups_name),
selected = "None"
),
selectInput(
inputId = "group2",
label = "Select a grouping variable",
choices = c("None", meta_groups_name),
selected = initial_group
),
radioButtons(
inputId = "coExp2",
label = "Calculate co-expression?",
choices = c("Yes", "No"),
selected = initial_coExp,
inline = TRUE
),
selectInput(
inputId = "palette2",
label = "Select a palette",
choices = names(palette_list),
selected = initial_palette2
),
selectInput(
inputId = "theme2",
label = "Select a theme",
choices = c("theme_scp", "theme_blank"),
selected = initial_theme2
),
selectInput(
inputId = "raster2",
label = "Raster",
choices = c("TRUE", "FALSE"),
selected = initial_raster
),
numericInput(
inputId = "size2",
label = "Panel size",
value = initial_size,
min = 1,
max = 10,
step = 0.1,
width = "150px"
),
numericInput(
inputId = "plot_dpi2",
label = "Resolution of the plot",
value = initial_dpi,
min = 50,
max = 1000,
step = 50,
width = "150px"
),
numericInput(
inputId = "ncol2",
label = "Number of columns",
value = initial_ncol,
min = 1,
max = 100,
step = 1,
width = "150px"
),
radioButtons(
inputId = "arrange2",
label = "Arrange by",
choices = c("Row", "Column"),
selected = initial_arrange,
inline = TRUE
),
actionButton(inputId = "submit2", label = "Submit", icon("play")),
helpText("Click the submit button to update the plot displayed in the right panel.")
),
mainPanel(
width = 9,
tabsetPanel(
tabPanel(
title = "2D plot",
column(
width = 12, offset = 0, style = "padding:0px;margin:0%",
div(
style = "overflow-x: auto;",
shinycssloaders::withSpinner(plotOutput("plot2", height = "100%", width = "100%"))
)
)
),
tabPanel(
title = "3D plot",
column(
width = 12, offset = 0, style = "padding:0px;margin:0%",
div(
style = "overflow-x: auto;",
shinycssloaders::withSpinner(plotly::plotlyOutput("plot2_3d", height = "100%", width = "100%"))
)
)
),
tabPanel(
title = "Violin plot",
column(
width = 12, offset = 0, style = "padding:0px;margin:0%",
div(
style = "overflow-x: auto;",
shinycssloaders::withSpinner(plotOutput("plot2_vln", height = "100%", width = "100%"))
)
)
)
)
)
)
)
)
# server ------------------------------------------------------------------
server <- function(input, output, session) {
# initial ----------------------------------------------------------------
updateSelectizeInput(session, "features2", choices = c(meta_features_name, all_features), selected = initial_feature, server = TRUE)
output$plot1 <- renderPlot(
{
initial_p1_dim
},
width = attr(initial_p1_dim, "size")$width * initial_dpi,
height = attr(initial_p1_dim, "size")$height * initial_dpi,
res = initial_dpi
)
output$plot1_3d <- plotly::renderPlotly(
{
initial_p1_3d
}
)
output$plot2 <- renderPlot(
{
initial_p2_dim
},
width = attr(initial_p2_dim, "size")$width * initial_dpi,
height = attr(initial_p2_dim, "size")$height * initial_dpi,
res = initial_dpi
)
output$plot2_3d <- plotly::renderPlotly(
{
initial_p2_3d
}
)
output$plot2_vln <- renderPlot(
{
initial_p2_vln
},
width = attr(initial_p2_vln, "size")$width * initial_dpi,
height = attr(initial_p2_vln, "size")$height * initial_dpi,
res = initial_dpi
)
# change dataset ----------------------------------------------------------------
observeEvent(input$dataset1, {
meta_groups_name <- rhdf5::h5read(MetaFile, name = paste0("/", input$dataset1, "/metadata.stat/asgroups"))
reduction_name <- meta_struc[meta_struc$group == paste0("/", input$dataset1, "/reductions"), "name"]
default_reduction <- as.character(rhdf5::h5read(MetaFile, name = paste0("/", input$dataset1, "/reductions.stat/Default_reduction")))
updateSelectInput(session, "reduction1", choices = reduction_name, selected = default_reduction)
updateSelectInput(session, "class1", choices = meta_groups_name, selected = "orig.ident")
updateSelectInput(session, "split1", choices = c("None", meta_groups_name), selected = "None")
})
observeEvent(input$dataset2, {
assays <- unique(na.omit(sapply(strsplit(data_group[grep(input$dataset2, data_group)], "/"), function(x) x[3])))
slots <- unique(na.omit(sapply(strsplit(data_group[grep(input$dataset2, data_group)], "/"), function(x) x[4])))
default_assay <- as.character(rhdf5::h5read(DataFile, name = paste0("/", input$dataset2, "/Default_assay")))
default_slot <- ifelse("data" %in% slots, "data", slots[1])
updateSelectInput(session, "assays2", choices = assays, selected = default_assay)
updateSelectInput(session, "slots2", choices = slots, selected = default_slot)
data <- HDF5Array::TENxMatrix(filepath = DataFile, group = paste0("/", input$dataset2, "/", default_assay, "/", default_slot))
all_features <- colnames(data)
meta_features_name <- rhdf5::h5read(MetaFile, name = paste0("/", input$dataset2, "/metadata.stat/asfeatures"))
meta_groups_name <- rhdf5::h5read(MetaFile, name = paste0("/", input$dataset2, "/metadata.stat/asgroups"))
reduction_name <- meta_struc[meta_struc$group == paste0("/", input$dataset2, "/reductions"), "name"]
default_reduction <- as.character(rhdf5::h5read(MetaFile, name = paste0("/", input$dataset2, "/reductions.stat/Default_reduction")))
updateSelectInput(session, "reduction2", choices = reduction_name, selected = default_reduction)
updateSelectizeInput(session, "features2",
choices = c(meta_features_name, all_features), selected = meta_features_name[1],
options = list(maxOptions = 20, maxItems = 20), server = TRUE
)
updateSelectInput(session, "split2", choices = c("None", meta_groups_name), selected = "None")
updateSelectInput(session, "group2", choices = meta_groups_name, selected = "orig.ident")
})
# submit1 ----------------------------------------------------------------
observeEvent(input$submit1, ignoreInit = FALSE, {
if (input$split1 == "None") {
split1 <- NULL
} else {
split1 <- input$split1
}
# message("DataFile:", DataFile)
# message("MetaFile:", MetaFile)
# message("input$dataset1:", input$dataset1)
# message("initial_slot:", initial_slot)
# message("c(input$class1, split1):", c(input$class1, split1))
# message("input$reduction1:", input$reduction1)
srt_tmp <- SCP::FetchH5(
DataFile = DataFile, MetaFile = MetaFile, name = input$dataset1,
features = NULL, slot = initial_slot, assay = NULL,
metanames = unique(c(input$class1, split1)), reduction = input$reduction1
)
raster1 <- input$raster1 == "TRUE"
p1_dim <- SCP::ClassDimPlot(