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Merge pull request #285 from hms-dbmi-cellenics/seurat-pipeline
Seurat pipeline
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| Original file line number | Diff line number | Diff line change |
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| #' Loads a Seurat object provided by the user | ||
| #' | ||
| #' This functions is a thin wrapper around `reconstruct_seurat`, which is used to | ||
| #' safely read, check, and reconstruct the Seurat object for downstream use. | ||
| #' | ||
| #' | ||
| #' @param input The input params received from the api. | ||
| #' @param pipeline_config List with S3 bucket name and SNS topics. | ||
| #' @param prev_out 'output' slot from call to \code{download_user_files} | ||
| #' @param input_dir A string, where the folder containing the downloaded | ||
| #' Seurat object is stored | ||
| #' | ||
| #' @export | ||
| load_seurat <- function(input, pipeline_config, prev_out, input_dir = "/input") { | ||
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| config <- prev_out$config | ||
| dataset_dir <- config$samples[1] | ||
| dataset_fpath <- file.path(input_dir, dataset_dir, 'r.rds') | ||
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| scdata <- reconstruct_seurat(dataset_fpath) | ||
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| prev_out$scdata <- scdata | ||
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| res <- list( | ||
| data = list(), | ||
| output = prev_out | ||
| ) | ||
| return(res) | ||
| } | ||
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| #' Reconstructs the Seurat object provided by the user | ||
| #' | ||
| #' The slots needed from the Seurat object are extracted and then their in-built types | ||
| #' are strictly checked before creating a new Seurat object. This reconstruction and type | ||
| #' checking prevents potentially malicious executable code (e.g. type `closure` or `environment`) | ||
| #' from being stored in the final Seurat object. | ||
| #' | ||
| #' @param dataset_fpath The path to the r.rds file containing the Seurat object. | ||
| #' | ||
| #' @return | ||
| #' @export | ||
| reconstruct_seurat <- function(dataset_fpath) { | ||
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| # read it | ||
| tryCatch({ | ||
| user_scdata <- readRDS(dataset_fpath) | ||
| stopifnot(methods::is(user_scdata, 'Seurat')) | ||
| }, | ||
| error = function(e) { | ||
| message(e$message) | ||
| stop(errors$ERROR_SEURAT_RDS, call. = FALSE) | ||
| }) | ||
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| # get counts | ||
| tryCatch({ | ||
| counts <- user_scdata[['RNA']]@counts | ||
| test_user_sparse_mat(counts) | ||
| rns <- row.names(counts) | ||
| check_type_is_safe(rns) | ||
| }, | ||
| error = function(e) { | ||
| message(e$message) | ||
| stop(errors$ERROR_SEURAT_COUNTS, call. = FALSE) | ||
| }) | ||
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| gene_annotations <- data.frame(input = rns, name = rns, original_name = rns, row.names = rns) | ||
| user_scdata@misc$gene_annotations <- gene_annotations | ||
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| # add dispersions | ||
| tryCatch({ | ||
| user_scdata <- add_dispersions(user_scdata) | ||
| dispersions <- user_scdata@misc$gene_dispersion | ||
| test_user_df(dispersions) | ||
| }, | ||
| error = function(e) { | ||
| message(e$message) | ||
| stop(errors$ERROR_SEURAT_HVFINFO, call. = FALSE) | ||
| }) | ||
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| # get meta data | ||
| tryCatch({ | ||
| metadata <- user_scdata@meta.data | ||
| test_user_df(metadata) | ||
| }, | ||
| error = function(e) { | ||
| message(e$message) | ||
| stop(errors$ERROR_SEURAT_METADATA, call. = FALSE) | ||
| }) | ||
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| # check for clusters | ||
| if (!'seurat_clusters' %in% colnames(metadata)) | ||
| stop(errors$ERROR_SEURAT_CLUSTERS, call. = FALSE) | ||
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| # reconstruct seurat object | ||
| scdata <- SeuratObject::CreateSeuratObject( | ||
| counts, | ||
| meta.data = metadata, | ||
| ) | ||
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| # add dispersions and gene annotations to new scdata | ||
| scdata@misc$gene_dispersion <- dispersions | ||
| scdata@misc$gene_annotations <- gene_annotations | ||
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| # add default dimensionality reduction | ||
| tryCatch({ | ||
| red_name <- SeuratObject::DefaultDimReduc(user_scdata) | ||
| check_type_is_safe(red_name) | ||
| embedding <- user_scdata@reductions[[red_name]]@cell.embeddings | ||
| test_user_df(embedding) | ||
| red <- SeuratObject::CreateDimReducObject( | ||
| embeddings = embedding, | ||
| assay = 'RNA' | ||
| ) | ||
| scdata@reductions[[red_name]] <- red | ||
| }, | ||
| error = function(e) { | ||
| message(e$message) | ||
| stop(errors$ERROR_SEURAT_REDUCTION, call. = FALSE) | ||
| }) | ||
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| # add pca dimensionality reduction | ||
| tryCatch({ | ||
| pca <- user_scdata@reductions[['pca']]@cell.embeddings | ||
| test_user_df(pca) | ||
| red <- SeuratObject::CreateDimReducObject( | ||
| embeddings = pca, | ||
| assay = 'RNA' | ||
| ) | ||
| scdata@reductions[['pca']] <- red | ||
| }, | ||
| error = function(e) { | ||
| message(e$message) | ||
| stop(errors$ERROR_SEURAT_REDUCTION, call. = FALSE) | ||
| }) | ||
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| # add logcounts | ||
| tryCatch({ | ||
| data <- user_scdata[['RNA']]@data | ||
| test_user_sparse_mat(data) | ||
| scdata[['RNA']]@data <- data | ||
| }, | ||
| error = function(e) { | ||
| message(e$message) | ||
| stop(errors$ERROR_SEURAT_LOGCOUNTS, call. = FALSE) | ||
| }) | ||
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| return(scdata) | ||
| } | ||
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| test_user_df <- function(df) { | ||
| for (col in colnames(df)) { | ||
| check_type_is_safe(df[, col]) | ||
| } | ||
| } | ||
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| test_user_sparse_mat <- function(counts) { | ||
| stopifnot(isS4(counts)) | ||
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| for (slot in methods::slotNames(counts)) { | ||
| check_type_is_safe(methods::slot(counts, slot)) | ||
| } | ||
| } | ||
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| check_type_is_safe <- function(x) { | ||
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| # typeof determines the R internal type or storage mode of any object | ||
| # whereas methods::is can be tricked by setting class inappropriately (e.g. disguising a function as a numeric) | ||
| safe.types <- c('character', 'double', 'integer', 'logical', 'NULL') | ||
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| # recurse into lists until reach node | ||
| if (typeof(x) == 'list') { | ||
| lapply(x, check_type_is_safe) | ||
| } else if (!typeof(x) %in% safe.types) { | ||
| stop('Unexpected data type in uploaded .rds file.') | ||
| } | ||
| } |
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