Reorganize datasets, separate out subset

R/datasets_nf.R

@@ -0,0 +1,122 @@
+#' Create datasets for Sarek-called somatic or germline variants results
+#'
+#' Organize variant call files from Nextflow Sarek into 3-4 datasets,
+#' grouping files by variant type and workflow with titles having the format:
+#' "{type} Genomic Variants - {workflow} Pipeline", e.g. "Somatic Genomic Variants - Strelka Pipeline".
+#' As you can see, this assumes that you want to create datasets that segregate Somatic and Germline calls.
+#' This makes sense for NF because Germline calls can be treated differently.
+#' This uses latest version of all files and creates a Draft version of the dataset.
+#'
+#' Since we basically just need the syn entity id, variant type, and workflow to group the files.
+#' Instead of getting this info through running `map_*` as in the example,
+#' you may prefer using a fileview, in which case you just need to download a table from a fileview
+#' that has `id` => `output_id` + the `dataType` and `workflow` annotations.
+#' The fileview can be used _after_ the files are annotated. If you want to create datasets _before_
+#' files are annotated, then you have to use `map_*`.
+#'
+#' Finally, datasets cannot use the same name if stored in the same project,
+#' so if there are multiple batches, the names will have to be made unique by adding
+#' the batch number, source data id, processing date, or whatever makes sense.
+#'
+#' @inheritParams new_dataset
+#' @param output_map The `data.table` returned from `map_sample_output_sarek`. See details for alternatives.
+#' @param workflow One of workflows used.
+#' @param verbose Optional, whether to be verbose -- defaults to TRUE.
+#' @import data.table
+#' @return A list of dataset objects.
+#' @export
+#' @examples
+#'\dontrun{
+#' syn_out <- "syn26648589"
+#' m <- map_sample_output_sarek(syn_out)
+#' datasets <- nf_sarek_datasets(m, parent = "syn26462036", dry_run = F) # use a test project
+#'}
+nf_sarek_datasets <- function(output_map,
+                              parent,
+                              workflow = c("FreeBayes", "Mutect2", "Strelka", "DeepVariant"),
+                              verbose = TRUE,
+                              dry_run = TRUE) {
+
+  output_map <- as.data.table(output_map)
+  if(!is.null(output_map$dataType)) {
+    data_type <- unique(output_map$dataType)
+    if(length(data_type) != 1) stop("Expecting one `dataType`, which does not appear to be the case.")
+    gvtype <- grep("(Germline|Somatic)Variants", data_type, value = T)
+    if(!length(gvtype)) stop("Data type does not look right, expecting either Germline or Somatic variants.")
+    gvtype <- switch(gvtype,
+                     SomaticVariants = "Somatic",
+                     GermlineVariants = "Germline")
+
+  } else {
+    # Detect genomic variants type from first path name
+    gvtype <- if(grepl("SomaticVariantCalls", first(output_map$caller_path))) {
+      "Somatic"
+    } else if(grepl("GermlineVariantCalls", first(output_map$caller_path)))  {
+      "Germline"
+    } else {
+      stop("Could not assign either Germline or Somatic labels based on main output folder.
+           Check whether folder contains mixed types or is not the right one.")
+    }
+  }
+  pattern <- "vcf.gz(.tbi)?$"
+  workflow <- match.arg(workflow)
+  datasets <- list()
+  for(i in workflow) {
+    dataset <- output_map[workflow == i & grepl(pattern, output_name)]
+    if(nrow(dataset)) {
+      if(verbose) glue::glue("Creating {i} dataset with {nrow(dataset)} files")
+      name <- glue::glue("{gvtype} Genomic Variants - {i} Pipeline")
+      dataset <- new_dataset(name = name, parent = parent, items = dataset$output_id, dry_run = TRUE)
+      if(dry_run) datasets[[i]] <- syn_dataset else datasets[[i]] <- .syn$store(syn_dataset)
+    }
+  }
+
+  return(datasets)
+
+}
+
+
+#' Create dataset for STAR-Salmon expression quantification results
+#'
+#' With a level-3 manifest that is created from `annotate_expression`,
+#' calls `new_dataset` to make quantification files (.sf) into dataset.
+#' Uses latest version of the files and creates a "Draft" dataset.
+#' See `nf_sarek_datasets`.
+#'
+#' @inheritParams new_dataset
+#' @inheritParams nf_sarek_datasets
+#' @param manifest A table of annotated data manifest from `annotate_expression`.
+#' @export
+nf_star_salmon_datasets <- function(manifest,
+                                    parent,
+                                    dry_run = TRUE) {
+
+  items <- manifest$entityId
+  new_dataset(name = "Gene Expression Quantification from RNA-seq",
+              parent = parent,
+              items = items,
+              dry_run = dry_run)
+}
+
+#' Create dataset for CNVKit results
+#'
+#' Create dataset from all files in CNVKit output
+#'
+#' @inheritParams new_dataset
+#' @param syn_out Output folder called 'cnvkit'
+#' @export
+nf_cnv_dataset <- function(syn_out,
+                           parent,
+                           dry_run = TRUE) {
+
+  files <- walk(syn_out)
+  files <- unlist(files)
+  df <- as.data.frame(matrix(files, ncol = 2, byrow = TRUE))
+  names(df) <- c("Filename", "id")
+  df <- df[grepl("cnr$|cns$|cnn$|bed$|pdf$|png$", df$Filename), ]
+  items <- df$id
+  new_dataset(name = "Copy Number Variant - CNVkit",
+              parent = parent,
+              items = items,
+              dry_run = dry_run)
+}