New version of GRaNIE integration

dockerfiles/granie/Dockerfile

@@ -2,16 +2,6 @@
 FROM  bioconductor/bioconductor_docker:devel-R-4.4.1
 
 
-# Install required dependencies for the R packages
-#RUN apt-get update && apt-get install -y \
-#    libcurl4-openssl-dev \
-#    libxml2-dev \
-#    libssl-dev \
-#    libcairo2-dev 
-#    libxt-dev \
-#    libopenblas-dev
-
-
 #Install R packages
 RUN R -e "install.packages(c('devtools'))"
 
@@ -21,19 +11,14 @@ WORKDIR /workspace
 # Default command
 CMD ["R"]
 
-RUN R -e "remotes::install_version('Matrix', version = '1.6-3')"
-
-#Version 1.9.4 of GRaNIE
-RUN R -e "devtools::install_gitlab('grp-zaugg/GRaNIE@855bf3def33ad7af9353db79c7e21c9279035fb8', host = 'git.embl.de', subdir = 'src/GRaNIE', dependencies = TRUE, upgrade = 'never')"
-
-#Version 0.2.1 of GRaNIEverse
-RUN R -e "devtools::install_gitlab('grp-zaugg/GRaNIEverse@3224b042f25f0085eeaf9194042bcb89103ea962', host = 'git.embl.de', upgrade = 'never', dependencies = TRUE)"
-
-#There seems to be an incompatibility with the Matrix and irlba package, downgrading Matrix seems to work
-
-RUN R -e "install.packages('irlba',type='source')"
-
-RUN R -e "BiocManager::install(c('BSgenome.Hsapiens.UCSC.hg38', 'EnsDb.Hsapiens.v86', 'EnsDb.Mmusculus.v79', 'BSgenome.Mmusculus.UCSC.mm39'))"
+#Version 1.9.4 of GRaNIE.
+RUN R -e "devtools::install_gitlab('grp-zaugg/[email protected]', host = 'git.embl.de', subdir = 'src/GRaNIE', dependencies = TRUE, upgrade = 'never')"
 
+#Version 0.3.1 of GRaNIEverse
+RUN R -e "devtools::install_gitlab('grp-zaugg/[email protected]', host = 'git.embl.de', upgrade = 'never', dependencies = TRUE)"
 
+#There is an incompatibility with the Matrix and irlba package, see https://github.com/satijalab/seurat/issues/8000
+RUN R -e "install.packages('irlba',type='source', rebuild = TRUE)"
 
+# biovizbase is only needed to create the ATAC assay along with annotation
+RUN R -e "BiocManager::install(c('BSgenome.Hsapiens.UCSC.hg38', 'EnsDb.Hsapiens.v86', 'EnsDb.Mmusculus.v79', 'BSgenome.Mmusculus.UCSC.mm39', 'biovizBase', 'Signac', 'glmGamPoi'))"

src/methods/multi_omics/granie/config.vsh.yaml

@@ -16,14 +16,63 @@ functionality:
     required: false
     direction: input
     description: "Path to the RNA data file (e.g., rna.rds)."
-    default: resources_test/grn-benchmark/multiomics_rna.rds
+    default: resources_test/grn-benchmark/multiomics_r/rna.rds
 
   - name: --file_atac
     type: file
     required: false
     direction: input
     description: "Path to the ATAC data file (e.g., atac.rds)."
-    default: resources_test/grn-benchmark/multiomics_atac.rds
+    default: resources_test/grn-benchmark/multiomics_r/atac.rds
+
+  - name: --normRNA
+    type: string
+    required: false
+    direction: input
+    description: Normalization method for RNA data.
+    default: "SCT"
+
+  - name: --normATAC
+    type: string
+    required: false
+    direction: input
+    description: Normalization method for ATAC data.
+    default: "LSI"
+
+  - name: --LSI_featureCutoff
+    type: string
+    required: false
+    direction: input
+    description: Feature cutoff for LSI normalization.
+    default: "q0"
+
+  - name: --nDimensions_ATAC
+    type: integer
+    required: false
+    direction: input
+    description: Number of dimensions for ATAC modality
+    default: 50
+
+  - name: --integrationMethod
+    type: string
+    required: false
+    direction: input
+    description: Method used for data integration.
+    default: "WNN"
+
+  - name: --WNN_knn
+    type: integer
+    required: false
+    direction: input
+    description: Number of nearest neighbors for WNN integration.
+    default: 20
+
+  - name: --minCellsPerCluster
+    type: integer
+    required: false
+    direction: input
+    description: Minimum number of cells required per cluster.
+    default: 25
 
 
   - name: --preprocessing_clusteringMethod
@@ -40,12 +89,12 @@ functionality:
     description: Resolution for clustering, typically between 5 and 20.
     default: 14
 
-  - name: --preprocessing_SCT_nDimensions
+  - name: --preprocessing_RNA_nDimensions
     type: integer
     required: false
     direction: input
     default: 50
-    description: Number of dimensions for SCT, default is 50.
+    description: Number of dimensions for RNA reduction, default is 50.
 
   - name: --genomeAssembly
     type: string
@@ -89,12 +138,13 @@ functionality:
     direction: input
     description: FDR threshold for peak-gene connections (default is 0.2).
 
-  - name: --peak_gene
-    type: file
-    required: false
-    direction: output
-    description: Path to the peak-gene output file (e.g., peak_gene.csv). Not yet implemented.
-    default: output/granie/peak_gene.csv
+  # Existance of output files is checked, not yet implemented
+  # - name: --peak_gene
+  #   type: file
+  #   required: false
+  #   direction: output
+  #   description: Path to the peak-gene output file (e.g., peak_gene.csv). Not yet implemented.
+  #   default: output/granie/peak_gene.csv
 
   - name: --useWeightingLinks
     type: boolean
@@ -110,14 +160,21 @@ functionality:
     direction: input
     description: "Flag to force rerun of the analysis regardless of existing results."
 
+  - name: --subset
+    type: boolean
+    required: false
+    default: false
+    direction: input
+    description: "Flag for testing purposes to subset the data for faster running times"
+
   resources:
     - type: r_script
       path: script.R
 
 
 platforms:
   - type: docker
-    image: chrarnold84/granieverse:latest
+    image: chrarnold84/granieverse:v1.3
 
   - type: native
   - type: nextflow

src/methods/multi_omics/granie/script.R

@@ -1,48 +1,55 @@
 
+## VIASH START
+# par <- list(
+#   file_rna = "resources_test/grn-benchmark/multiomics_r/rna.rds",
+#   file_atac = "resources_test/grn-benchmark/multiomics_r/atac.rds",
+#   preprocessing_clusteringMethod = 1, # Seurat::FindClusters: (1 = original Louvain algorithm, 2 = Louvain algorithm with multilevel refinement, 3 = SLM algorithm, 4 = Leiden algorithm)
+#   preprocessing_clusterResolution = 14, # Typically between 5 and 20
+#   preprocessing_RNA_nDimensions = 50, # Default 50
+#   genomeAssembly = "hg38",
+#   GRaNIE_corMethod = "spearman",
+#   GRaNIE_includeSexChr = TRUE,
+#   GRaNIE_promoterRange = 250000,
+#   GRaNIE_TF_peak_fdr_threshold = 0.2,
+#   GGRaNIE_peak_gene_fdr_threshold = 0.2,
+#   num_workers = 4,
+#   peak_gene = "output/granie/peak_gene.csv", # not yet implemented, should I?
+#   prediction= "output/granie/prediction.csv",
+#   useWeightingLinks = FALSE,
+#   forceRerun = FALSE
+# )
+
+# meta <- list(
+#   functionality_name = "my_method_r"
+# )
+## VIASH END
+
 set.seed(42)
+suppressPackageStartupMessages(library(Seurat))
 
-library(Seurat)
-library(Signac)
-library(Matrix)
+suppressPackageStartupMessages(library(Signac))
+suppressPackageStartupMessages(library(Matrix))
 library(GRaNIEverse)
 library(GRaNIE)
-library(qs)
-library(BSgenome.Hsapiens.UCSC.hg38)
-library(EnsDb.Hsapiens.v86)
-library(EnsDb.Mmusculus.v79)
-library(BSgenome.Mmusculus.UCSC.mm39)
-library(dplyr)
+suppressPackageStartupMessages(library(qs))
+suppressPackageStartupMessages(library(BSgenome.Hsapiens.UCSC.hg38))
+suppressPackageStartupMessages(library(EnsDb.Hsapiens.v86))
+suppressPackageStartupMessages(library(EnsDb.Mmusculus.v79))
+suppressPackageStartupMessages(library(BSgenome.Mmusculus.UCSC.mm39))
+suppressPackageStartupMessages(library(dplyr))
+suppressPackageStartupMessages(library(SummarizedExperiment))
+
+
+cat("Content of par list:")
+str(par)
+
+#qs::qsave(par, "/home/carnold/par.qs")
 
-## VIASH START
-par <- list(
-  file_rna = "resources_test/grn-benchmark/multiomics_r/rna.rds",
-  file_atac = "resources_test/grn-benchmark/multiomics_r/atac.rds",
-  temp_dir =  "output/granie/",
-  preprocessing_clusteringMethod = 1, # Seurat::FindClusters: (1 = original Louvain algorithm, 2 = Louvain algorithm with multilevel refinement, 3 = SLM algorithm, 4 = Leiden algorithm)
-  preprocessing_clusterResolution = 14, # Typically between 5 and 20
-  preprocessing_SCT_nDimensions = 50, # Default 50
-  genomeAssembly = "hg38",
-  GRaNIE_corMethod = "spearman",
-  GRaNIE_includeSexChr = TRUE,
-  GRaNIE_promoterRange = 250000,
-  GRaNIE_TF_peak_fdr_threshold = 0.2,
-  GRaNIE_peak_gene_fdr_threshold = 0.2,
-  num_workers = 4,
-  peak_gene = "output/granie/peak_gene.csv", # not yet implemented, should I?
-  prediction= "output/granie/prediction.csv",
-  useWeightingLinks = FALSE,
-  forceRerun = FALSE
-)
-## VIASH END
-print(par)
-# meta <- list(
-#   functionality_name = "my_method_r"
-# )
 
 
 #### STANDARD ASSIGNMENTS ###
 file_seurat = "seurat_granie.qs"
-outputDir = par$temp_dir
+outputDir = dirname(par$prediction)
 
 if (!dir.exists(outputDir)) {
   dir.create(outputDir, recursive = TRUE)
@@ -67,7 +74,7 @@ if (!file.exists(destfile)) {
 # Define the directory to extract the files to
 exdir <- "PWMScan_HOCOMOCOv12_H12INVIVO"
 
-GRaNIE_TFBSFolder = paste0(exdir, "/PWMScan_HOCOMOCOv12/H12INVIVO")
+GRaNIE_TFBSFolder = paste0(exdir, "/H12INVIVO")
 
 if (!file.exists(GRaNIE_TFBSFolder)) {
   untar(destfile, exdir = exdir)
@@ -91,7 +98,7 @@ if (!file.exists(file_RNA)) {
 # Preprocess data #
 ###################
 
-if (par.l$forceRerun | !file.exists(file_seurat)) {
+if (par$forceRerun | !file.exists(file_seurat)) {
 
  # Sparse matrix
  rna.m = readRDS(par$file_rna)
@@ -146,12 +153,6 @@ if (par.l$forceRerun | !file.exists(file_seurat)) {
 }
 
 output_seuratProcessed = paste0(outputDir, "/seuratObject.qs")
-if (!file.exists(output_seuratProcessed)) {
-  prepareData = TRUE
-} else {
-  prepareData = FALSE
-}
-
 
 ###################
 # Preprocess data #
@@ -162,24 +163,38 @@ GRaNIE_file_peaks = paste0(outputDir, "/atac.pseudobulkFromClusters_res", par$pr
 GRaNIE_file_rna = paste0(outputDir, "/rna.pseudobulkFromClusters_res", par$preprocessing_clusterResolution, "_mean.tsv.gz")
 GRaNIE_file_metadata = paste0(outputDir, "/metadata_res", par$preprocessing_clusterResolution, "_mean.tsv.gz")
 
-if (file.exists(GRaNIE_file_peaks) & file.exists(GRaNIE_file_metadata) & file.exists(GRaNIE_file_rna) & !par.l$forceRerun) {
+if (file.exists(GRaNIE_file_peaks) & file.exists(GRaNIE_file_metadata) & file.exists(GRaNIE_file_rna) & !par$forceRerun) {
 
-  cat("Preprocessing skipped because all files alreadx exist anf forceRerun = FALSE.")
+  cat("Preprocessing skipped because all files already exist anf forceRerun = FALSE.")
 
 } else {
-
+
+    # Subset for testing purposes
+    if (par$subset == TRUE) {
+        cat("SUBSET cells\n")
+        random_cells <- sample(Cells(seurat_object), size = 5000, replace = FALSE)
+        seurat_object = subset(seurat_object, cells = random_cells)
+        cat("SUBSET peaks\n")
+        peak_names <- rownames(seurat_object[["peaks"]])
+        selected_peaks <- sample(peak_names, size = 50000, replace = FALSE)
+        seurat_object[["peaks"]] = subset(seurat_object[["peaks"]], features = selected_peaks)
+    }
+
   seurat_object = prepareSeuratData_GRaNIE(seurat_object, 
-                                           outputDir = par$outputDir,
-                                           file_RNA_features = file_RNA, 
-                                           assayName_RNA_raw = "RNA", assayName_ATAC = "peaks", 
-                                           prepareData = prepareData, 
-                                           SCT_nDimensions = par$preprocessing_SCT_nDimensions, 
-                                           dimensionsToIgnore_LSI_ATAC = 1,
+                                           outputDir = outputDir,
+                                           saveSeuratObject = TRUE,
+                                           genome = par$genomeAssembly,
+                                           assayName_RNA = "RNA", normRNA = "SCT", nDimensions_RNA = par$preprocessing_RNA_nDimensions, recalculateVariableFeatures = NULL,
+                                           assayName_ATAC_raw = "peaks", 
+                                           normATAC = "LSI", LSI_featureCutoff = "q0", nDimensions_ATAC = 50, dimensionsToIgnore_LSI_ATAC = 1,
+                                           integrationMethod = "WNN", WNN_knn = 20,
                                            pseudobulk_source = "cluster",
                                            countAggregation = "mean",
                                            clusteringAlgorithm = par$preprocessing_clusteringMethod, 
-                                           clusterResolutions = par$preprocessing_clusterResolution, 
-                                           saveSeuratObject = TRUE)
+                                           clusterResolutions = par$preprocessing_clusterResolution,
+                                           minCellsPerCluster = 25,
+                                           forceRerun = FALSE
+      )
 
 }
 
@@ -190,7 +205,7 @@ if (file.exists(GRaNIE_file_peaks) & file.exists(GRaNIE_file_metadata) & file.ex
 ##############
 
 GRN = runGRaNIE(
-  dir_output = par$temp_dir,
+  dir_output = outputDir,
   datasetName = "undescribed",
   GRaNIE_file_peaks,
   GRaNIE_file_rna,