cwlVersion: v1.0 class: Workflow requirements: - class: SubworkflowFeatureRequirement - class: StepInputExpressionRequirement - class: MultipleInputFeatureRequirement - class: InlineJavascriptRequirement expressionLib: - var split_features = function(line) { function get_unique(value, index, self) { return self.indexOf(value) === index && value != ""; } let splitted_line = line?line.split(/[\s,]+/).filter(get_unique):null; return (splitted_line && !!splitted_line.length)?splitted_line:null; }; - var split_numbers = function(line) { let splitted_line = line?line.split(/[\s,]+/).map(parseFloat):null; return (splitted_line && !!splitted_line.length)?splitted_line:null; }; 'sd:upstream': sc_rnaseq_aggr_sample: - "cellranger-aggr.cwl" inputs: alias: type: string label: "Experiment short name/Alias" sd:preview: position: 1 filtered_feature_bc_matrix_folder: type: File label: "scRNA-Seq Cellranger Aggregate Experiment" doc: | Compressed folder with aggregated filtered feature-barcode matrices in MEX format 'sd:upstreamSource': "sc_rnaseq_aggr_sample/filtered_feature_bc_matrix_folder" 'sd:localLabel': true aggregation_metadata: type: File label: "scRNA-Seq Cellranger Aggregate Experiment" doc: | Aggregation metadata in CSV format 'sd:upstreamSource': "sc_rnaseq_aggr_sample/aggregation_metadata" 'sd:localLabel': true minimum_cells: type: int? default: 5 label: "Include genes detected in at least this many cells" doc: | Include genes detected in at least this many cells (applied to thoughout all datasets together). 'sd:layout': advanced: true minimum_features: type: string? default: "250" label: "Include cells where at least this many genes are detected" doc: | Include cells where at least this many genes are detected. If multiple values provided each of them will be applied to the correspondent dataset. 'sd:layout': advanced: true maximum_features: type: string? default: "5000" label: "Include cells with the number of genes not bigger than this value" doc: | Include cells with the number of genes not bigger than this value. If multiple values provided each of them will be applied to the correspondent dataset. 'sd:layout': advanced: true minimum_umis: type: string? default: "500" label: "Include cells where at least this many UMIs are detected" doc: | Include cells where at least this many UMIs are detected. If multiple values provided each of them will be applied to the correspondent dataset. 'sd:layout': advanced: true minimum_novelty_score: type: string? default: "0.8" label: "Include cells with the novelty score (the ratio of genes per cell over UMIs per cell) not lower than this value" doc: | Include cells with the novelty score (the ratio of genes per cell over UMIs per cell) not lower than this value (calculated as log10(genes)/log10(UMIs)). If multiple values provided each of them will be applied to the correspondent dataset. 'sd:layout': advanced: true maximum_mito_perc: type: float? default: 5 label: "Include cells with the percentage of transcripts mapped to mitochondrial genes not bigger than this value" doc: | Include cells with the percentage of transcripts mapped to mitochondrial genes not bigger than this value. 'sd:layout': advanced: true mito_pattern: type: string? default: "^Mt-" label: "Pattern to identify mitochondrial genes" doc: | Pattern to identify mitochondrial genes. 'sd:layout': advanced: true high_var_features_count: type: int? default: 3000 label: "Number of highly variable genes to detect (used for dataset integration and dimensional reduction)" doc: | Number of highly variable genes to detect (used for dataset integration and dimensional reduction). 'sd:layout': advanced: true dimensionality: type: int? default: 10 label: "Number of principal components to use in UMAP projection and clustering (from 1 to 50)" doc: | Number of principal components to use in UMAP projection and clustering (from 1 to 50). Use Elbow plot to adjust this parameter. 'sd:layout': advanced: true umap_spread: type: float? default: 1 label: "Effective scale of embedded points on UMAP. Determines how clustered/clumped the embedded points are." doc: | The effective scale of embedded points on UMAP. In combination with mindist this determines how clustered/clumped the embedded points are. 'sd:layout': advanced: true umap_mindist: type: float? default: 0.3 label: "Controls how tightly the embedding is allowed compress points together on UMAP. Sensible values are in the range 0.001 to 0.5" doc: | Controls how tightly the embedding is allowed compress points together on UMAP. Larger values ensure embedded points are moreevenly distributed, while smaller values allow the algorithm to optimise more accurately with regard to local structure. Sensible values are in the range 0.001 to 0.5. 'sd:layout': advanced: true umap_nneighbors: type: int? default: 30 label: "Number of neighboring points used in UMAP. Larger values result in loss of detailed local structure." doc: | Determines the number of neighboring points used in UMAP. Larger values will result in more global structure being preserved at the loss of detailed local structure. In general this parameter should often be in the range 5 to 50. 'sd:layout': advanced: true umap_metric: type: - "null" - type: enum symbols: - "euclidean" - "manhattan" - "chebyshev" - "minkowski" - "canberra" - "braycurtis" - "mahalanobis" - "wminkowski" - "seuclidean" - "cosine" - "correlation" - "haversine" - "hamming" - "jaccard" - "dice" - "russelrao" - "kulsinski" - "ll_dirichlet" - "hellinger" - "rogerstanimoto" - "sokalmichener" - "sokalsneath" - "yule" default: "cosine" label: "The metric to use to compute distances in high dimensional space for UMAP" doc: | The metric to use to compute distances in high dimensional space for UMAP. 'sd:layout': advanced: true umap_method: type: - "null" - type: enum symbols: - "uwot" - "uwot-learn" - "umap-learn" default: "uwot" label: "UMAP implementation to run" doc: | UMAP implementation to run. 'sd:layout': advanced: true cluster_metric: type: - "null" - type: enum symbols: - "euclidean" - "cosine" - "manhattan" - "hamming" default: "euclidean" label: "Distance metric used by the nearest neighbors algorithm when running clustering" doc: | Distance metric used by the nearest neighbors algorithm when running clustering. 'sd:layout': advanced: true resolution: type: string? default: "0.1" label: "Comma or space separated list of clustering resolutions" doc: | Comma or space separated list of clustering resolutions 'sd:layout': advanced: true minimum_logfc: type: float? default: 0.25 label: "Include only those genes that on average have log fold change difference in expression between every tested pair of clusters not lower than this value" doc: | Include only those genes that on average have log fold change difference in expression between every tested pair of clusters not lower than this value. 'sd:layout': advanced: true minimum_pct: type: float? default: 0.1 label: "Include only those genes that are detected in not lower than this fraction of cells in either of the two tested clusters" doc: | Include only those genes that are detected in not lower than this fraction of cells in either of the two tested clusters. 'sd:layout': advanced: true test_use: type: - "null" - type: enum symbols: - "wilcox" - "bimod" - "roc" - "t" - "negbinom" - "poisson" - "LR" - "MAST" - "DESeq2" default: "wilcox" label: "Statistical test to use for gene markers identification" doc: | Statistical test to use for gene markers identification. 'sd:layout': advanced: true threads: type: int? default: 6 label: "Threads number to use" doc: | Threads number 'sd:layout': advanced: true species: type: - "null" - type: enum symbols: - "hs" - "mm" - "none" default: "none" label: "Species for gene name conversion when running cell type prediction" doc: | Select species for gene name conversion when running cell type prediction with Garnett classifier. If "none" - do not convert gene names 'sd:layout': advanced: true regress_cellcycle: type: boolean? default: false label: "Regress cell cycle as a confounding source of variation" doc: | Regress cell cycle as a confounding source of variation. 'sd:layout': advanced: true regress_mito_perc: type: boolean? default: false label: "Regress mitochondrial gene expression as a confounding source of variation" doc: | Regress mitochondrial gene expression as a confounding source of variation. 'sd:layout': advanced: true only_positive_markers: type: boolean? default: false label: "Report only positive gene markers" doc: | Report only positive gene markers. 'sd:layout': advanced: true no_sct: type: boolean? default: false label: "Use LogNormalize instead of SCTransform when integrating datasets" doc: | Do not use SCTransform when running datasets integration. Use LogNormalize instead. 'sd:layout': advanced: true selected_features: type: string? default: null label: "Comma or space separated list of genes of interest" doc: | Comma or space separated list of genes of interest. Default: do not highlight any features 'sd:layout': advanced: true conditions_data: type: File? label: "TSV/CSV file to define datasets conditions with 'library_id' and 'condition' columns. Rows order should correspond to the aggregation metadata." doc: | Path to the TSV/CSV file to define datasets grouping. First column - 'library_id' with the values provided in the same order as in the correspondent column of the --identity file, second column 'condition'. If not provided, each dataset is assigned to its own biological condition barcodes_data: type: File? label: "Headerless TSV/CSV file with cell barcodes (one barcode per line) to prefilter input data" doc: | Path to the headerless TSV/CSV file with selected barcodes (one per line) to prefilter input feature-barcode matrices. If not provided, use all cells 'sd:layout': advanced: true cell_cycle_data: type: File? label: "TSV/CSV file with cell cycle data with 'phase' and 'gene_id' columns" doc: | TSV/CSV file with cell cycle data. First column - 'phase', second column 'gene_id'. If not provided, skip cell cycle score assignment 'sd:layout': advanced: true classifier_rds: type: File? label: "Garnett classifier rds file for cell type prediction" doc: | Path to the Garnett classifier rds file for cell type prediction. If not provided, skip cell type prediction 'sd:layout': advanced: true outputs: raw_cell_count_plot_png: type: File? outputSource: seurat_cluster/raw_cell_count_plot_png label: "Number of cells per dataset (not filtered)" doc: | Number of cells per dataset (not filtered). PNG format 'sd:visualPlugins': - image: tab: 'QC (not filtered)' Caption: 'Number of cells per dataset (not filtered)' raw_cell_count_plot_pdf: type: File? outputSource: seurat_cluster/raw_cell_count_plot_pdf label: "Number of cells per dataset (not filtered)" doc: | Number of cells per dataset (not filtered). PDF format raw_umi_dnst_spl_by_cond_plot_png: type: File? outputSource: seurat_cluster/raw_umi_dnst_spl_by_cond_plot_png label: "Split by condition UMI density per cell (not filtered)" doc: | Split by condition UMI density per cell (not filtered). PNG format 'sd:visualPlugins': - image: tab: 'QC (not filtered)' Caption: 'Split by condition UMI density per cell (not filtered)' raw_umi_dnst_spl_by_cond_plot_pdf: type: File? outputSource: seurat_cluster/raw_umi_dnst_spl_by_cond_plot_pdf label: "Split by condition UMI density per cell (not filtered)" doc: | Split by condition UMI density per cell (not filtered). PDF format raw_gene_dnst_spl_by_cond_plot_png: type: File? outputSource: seurat_cluster/raw_gene_dnst_spl_by_cond_plot_png label: "Split by condition gene density per cell (not filtered)" doc: | Split by condition gene density per cell (not filtered). PNG format 'sd:visualPlugins': - image: tab: 'QC (not filtered)' Caption: 'Split by condition gene density per cell (not filtered)' raw_gene_dnst_spl_by_cond_plot_pdf: type: File? outputSource: seurat_cluster/raw_gene_dnst_spl_by_cond_plot_pdf label: "Split by condition gene density per cell (not filtered)" doc: | Split by condition gene density per cell (not filtered). PDF format raw_gene_umi_corr_spl_by_ident_plot_png: type: File? outputSource: seurat_cluster/raw_gene_umi_corr_spl_by_ident_plot_png label: "Split by identity genes vs UMIs per cell correlation (not filtered)" doc: | Split by identity genes vs UMIs per cell correlation (not filtered). PNG format 'sd:visualPlugins': - image: tab: 'QC (not filtered)' Caption: 'Split by identity genes vs UMIs per cell correlation (not filtered)' raw_gene_umi_corr_spl_by_ident_plot_pdf: type: File? outputSource: seurat_cluster/raw_gene_umi_corr_spl_by_ident_plot_pdf label: "Split by identity genes vs UMIs per cell correlation (not filtered)" doc: | Split by identity genes vs UMIs per cell correlation (not filtered). PDF format raw_mito_perc_dnst_spl_by_cond_plot_png: type: File? outputSource: seurat_cluster/raw_mito_perc_dnst_spl_by_cond_plot_png label: "Split by condition density of transcripts mapped to mitochondrial genes per cell (not filtered)" doc: | Split by condition density of transcripts mapped to mitochondrial genes per cell (not filtered). PNG format 'sd:visualPlugins': - image: tab: 'QC (not filtered)' Caption: 'Split by condition density of transcripts mapped to mitochondrial genes per cell (not filtered)' raw_mito_perc_dnst_spl_by_cond_plot_pdf: type: File? outputSource: seurat_cluster/raw_mito_perc_dnst_spl_by_cond_plot_pdf label: "Split by condition density of transcripts mapped to mitochondrial genes per cell (not filtered)" doc: | Split by condition density of transcripts mapped to mitochondrial genes per cell (not filtered). PDF format raw_nvlt_score_dnst_spl_by_cond_plot_png: type: File? outputSource: seurat_cluster/raw_nvlt_score_dnst_spl_by_cond_plot_png label: "Split by condition novelty score density per cell (not filtered)" doc: | Split by condition novelty score density per cell (not filtered). PNG format 'sd:visualPlugins': - image: tab: 'QC (not filtered)' Caption: 'Split by condition novelty score density per cell (not filtered)' raw_nvlt_score_dnst_spl_by_cond_plot_pdf: type: File? outputSource: seurat_cluster/raw_nvlt_score_dnst_spl_by_cond_plot_pdf label: "Split by condition novelty score density per cell (not filtered)" doc: | Split by condition novelty score density per cell (not filtered). PDF format raw_qc_mtrcs_plot_png: type: File? outputSource: seurat_cluster/raw_qc_mtrcs_plot_png label: "QC metrics densities per cell (not filtered)" doc: | QC metrics densities per cell (not filtered). PNG format 'sd:visualPlugins': - image: tab: 'QC (not filtered)' Caption: 'QC metrics densities per cell (not filtered)' raw_qc_mtrcs_plot_pdf: type: File? outputSource: seurat_cluster/raw_qc_mtrcs_plot_pdf label: "QC metrics densities per cell (not filtered)" doc: | QC metrics densities per cell (not filtered). PDF format raw_qc_mtrcs_gr_by_cond_plot_png: type: File? outputSource: seurat_cluster/raw_qc_mtrcs_gr_by_cond_plot_png label: "Grouped by condition QC metrics densities per cell (not filtered)" doc: | Grouped by condition QC metrics densities per cell (not filtered). PNG format 'sd:visualPlugins': - image: tab: 'QC (not filtered)' Caption: 'Grouped by condition QC metrics densities per cell (not filtered)' raw_qc_mtrcs_gr_by_cond_plot_pdf: type: File? outputSource: seurat_cluster/raw_qc_mtrcs_gr_by_cond_plot_pdf label: "Grouped by condition QC metrics densities per cell (not filtered)" doc: | Grouped by condition QC metrics densities per cell (not filtered). PDF format fltr_cell_count_plot_png: type: File? outputSource: seurat_cluster/fltr_cell_count_plot_png label: "Number of cells per dataset (filtered)" doc: | Number of cells per dataset (filtered). PNG format 'sd:visualPlugins': - image: tab: 'QC (filtered)' Caption: 'Number of cells per dataset (filtered)' fltr_cell_count_plot_pdf: type: File? outputSource: seurat_cluster/fltr_cell_count_plot_pdf label: "Number of cells per dataset (filtered)" doc: | Number of cells per dataset (filtered). PDF format fltr_umi_dnst_spl_by_cond_plot_png: type: File? outputSource: seurat_cluster/fltr_umi_dnst_spl_by_cond_plot_png label: "Split by condition UMI density per cell (filtered)" doc: | Split by condition UMI density per cell (filtered). PNG format 'sd:visualPlugins': - image: tab: 'QC (filtered)' Caption: 'Split by condition UMI density per cell (filtered)' fltr_umi_dnst_spl_by_cond_plot_pdf: type: File? outputSource: seurat_cluster/fltr_umi_dnst_spl_by_cond_plot_pdf label: "Split by condition UMI density per cell (filtered)" doc: | Split by condition UMI density per cell (filtered). PDF format fltr_gene_dnst_spl_by_cond_plot_png: type: File? outputSource: seurat_cluster/fltr_gene_dnst_spl_by_cond_plot_png label: "Split by condition gene density per cell (filtered)" doc: | Split by condition gene density per cell (filtered). PNG format 'sd:visualPlugins': - image: tab: 'QC (filtered)' Caption: 'Split by condition gene density per cell (filtered)' fltr_gene_dnst_spl_by_cond_plot_pdf: type: File? outputSource: seurat_cluster/fltr_gene_dnst_spl_by_cond_plot_pdf label: "Split by condition gene density per cell (filtered)" doc: | Split by condition gene density per cell (filtered). PDF format fltr_gene_umi_corr_spl_by_ident_plot_png: type: File? outputSource: seurat_cluster/fltr_gene_umi_corr_spl_by_ident_plot_png label: "Split by identity genes vs UMIs per cell correlation (filtered)" doc: | Split by identity genes vs UMIs per cell correlation (filtered). PNG format 'sd:visualPlugins': - image: tab: 'QC (filtered)' Caption: 'Split by identity genes vs UMIs per cell correlation (filtered)' fltr_gene_umi_corr_spl_by_ident_plot_pdf: type: File? outputSource: seurat_cluster/fltr_gene_umi_corr_spl_by_ident_plot_pdf label: "Split by identity genes vs UMIs per cell correlation (filtered)" doc: | Split by identity genes vs UMIs per cell correlation (filtered). PDF format fltr_mito_perc_dnst_spl_by_cond_plot_png: type: File? outputSource: seurat_cluster/fltr_mito_perc_dnst_spl_by_cond_plot_png label: "Split by condition density of transcripts mapped to mitochondrial genes per cell (filtered)" doc: | Split by condition density of transcripts mapped to mitochondrial genes per cell (filtered). PNG format 'sd:visualPlugins': - image: tab: 'QC (filtered)' Caption: 'Split by condition density of transcripts mapped to mitochondrial genes per cell (filtered)' fltr_mito_perc_dnst_spl_by_cond_plot_pdf: type: File? outputSource: seurat_cluster/fltr_mito_perc_dnst_spl_by_cond_plot_pdf label: "Split by condition density of transcripts mapped to mitochondrial genes per cell (filtered)" doc: | Split by condition density of transcripts mapped to mitochondrial genes per cell (filtered). PDF format fltr_nvlt_score_dnst_spl_by_cond_plot_png: type: File? outputSource: seurat_cluster/fltr_nvlt_score_dnst_spl_by_cond_plot_png label: "Split by condition novelty score density per cell (filtered)" doc: | Split by condition novelty score density per cell (filtered). PNG format 'sd:visualPlugins': - image: tab: 'QC (filtered)' Caption: 'Split by condition novelty score density per cell (filtered)' fltr_nvlt_score_dnst_spl_by_cond_plot_pdf: type: File? outputSource: seurat_cluster/fltr_nvlt_score_dnst_spl_by_cond_plot_pdf label: "Split by condition novelty score density per cell (filtered)" doc: | Split by condition novelty score density per cell (filtered). PDF format fltr_qc_mtrcs_plot_png: type: File? outputSource: seurat_cluster/fltr_qc_mtrcs_plot_png label: "QC metrics densities per cell (filtered)" doc: | QC metrics densities per cell (filtered). PNG format 'sd:visualPlugins': - image: tab: 'QC (filtered)' Caption: 'QC metrics densities per cell (filtered)' fltr_qc_mtrcs_plot_pdf: type: File? outputSource: seurat_cluster/fltr_qc_mtrcs_plot_pdf label: "QC metrics densities per cell (filtered)" doc: | QC metrics densities per cell (filtered). PDF format fltr_qc_mtrcs_gr_by_cond_plot_png: type: File? outputSource: seurat_cluster/fltr_qc_mtrcs_gr_by_cond_plot_png label: "Grouped by condition QC metrics densities per cell (filtered)" doc: | Grouped by condition QC metrics densities per cell (filtered). PDF format 'sd:visualPlugins': - image: tab: 'QC (filtered)' Caption: 'Grouped by condition QC metrics densities per cell (filtered)' fltr_qc_mtrcs_gr_by_cond_plot_pdf: type: File? outputSource: seurat_cluster/fltr_qc_mtrcs_gr_by_cond_plot_pdf label: "Grouped by condition QC metrics densities per cell (filtered)" doc: | Grouped by condition QC metrics densities per cell (filtered). PDF format fltr_pca_spl_by_ph_plot_png: type: File? outputSource: seurat_cluster/fltr_pca_spl_by_ph_plot_png label: "Split by cell cycle phase PCA of filtered unintegrated/scaled datasets" doc: | Split by cell cycle phase PCA of filtered unintegrated/scaled datasets. PNG format 'sd:visualPlugins': - image: tab: 'QC (filtered)' Caption: 'Split by cell cycle phase PCA of filtered unintegrated/scaled datasets' fltr_pca_spl_by_ph_plot_pdf: type: File? outputSource: seurat_cluster/fltr_pca_spl_by_ph_plot_pdf label: "Split by cell cycle phase PCA of filtered unintegrated/scaled datasets" doc: | Split by cell cycle phase PCA of filtered unintegrated/scaled datasets. PDF format fltr_pca_spl_by_mito_perc_plot_png: type: File? outputSource: seurat_cluster/fltr_pca_spl_by_mito_perc_plot_png label: "Split by level of transcripts mapped to mitochondrial genes PCA of filtered unintegrated/scaled datasets" doc: | Split by level of transcripts mapped to mitochondrial genes PCA of filtered unintegrated/scaled datasets. PNG format 'sd:visualPlugins': - image: tab: 'QC (filtered)' Caption: 'Split by level of transcripts mapped to mitochondrial genes PCA of filtered unintegrated/scaled datasets' fltr_pca_spl_by_mito_perc_plot_pdf: type: File? outputSource: seurat_cluster/fltr_pca_spl_by_mito_perc_plot_pdf label: "Split by level of transcripts mapped to mitochondrial genes PCA of filtered unintegrated/scaled datasets" doc: | Split by level of transcripts mapped to mitochondrial genes PCA of filtered unintegrated/scaled datasets. PDF format fltr_umap_spl_by_idnt_plot_png: type: File? outputSource: seurat_cluster/fltr_umap_spl_by_idnt_plot_png label: "Split by identity UMAP projected PCA of filtered unintegrated/scaled datasets" doc: | Split by identity UMAP projected PCA of filtered unintegrated/scaled datasets. PNG format 'sd:visualPlugins': - image: tab: 'QC (filtered)' Caption: 'Split by identity UMAP projected PCA of filtered unintegrated/scaled datasets' fltr_umap_spl_by_idnt_plot_pdf: type: File? outputSource: seurat_cluster/fltr_umap_spl_by_idnt_plot_pdf label: "Split by identity UMAP projected PCA of filtered unintegrated/scaled datasets" doc: | Split by identity UMAP projected PCA of filtered unintegrated/scaled datasets. PDF format ntgr_elbow_plot_png: type: File? outputSource: seurat_cluster/ntgr_elbow_plot_png label: "Elbow plot from PCA of filtered integrated/scaled datasets" doc: | Elbow plot from PCA of filtered integrated/scaled datasets. PNG format 'sd:visualPlugins': - image: tab: 'Dimensionality evaluation' Caption: 'Elbow plot from PCA of filtered integrated/scaled datasets' ntgr_elbow_plot_pdf: type: File? outputSource: seurat_cluster/ntgr_elbow_plot_pdf label: "Elbow plot from PCA of filtered integrated/scaled datasets" doc: | Elbow plot from PCA of filtered integrated/scaled datasets. PDF format ntgr_pca_plot_png: type: File? outputSource: seurat_cluster/ntgr_pca_plot_png label: "PCA of filtered integrated/scaled datasets" doc: | PCA of filtered integrated/scaled datasets. PNG format 'sd:visualPlugins': - image: tab: 'Dimensionality evaluation' Caption: 'PCA of filtered integrated/scaled datasets' ntgr_pca_plot_pdf: type: File? outputSource: seurat_cluster/ntgr_pca_plot_pdf label: "PCA of filtered integrated/scaled datasets" doc: | PCA of filtered integrated/scaled datasets. PDF format ntgr_pca_heatmap_png: type: File? outputSource: seurat_cluster/ntgr_pca_heatmap_png label: "Genes per cells expression heatmap sorted by their PC scores from PCA of filtered integrated/scaled datasets" doc: | Genes per cells expression heatmap sorted by their PC scores from PCA of filtered integrated/scaled datasets. PNG format 'sd:visualPlugins': - image: tab: 'Dimensionality evaluation' Caption: 'Genes per cells expression heatmap sorted by their PC scores from PCA of filtered integrated/scaled datasets' ntgr_pca_heatmap_pdf: type: File? outputSource: seurat_cluster/ntgr_pca_heatmap_pdf label: "Genes per cells expression heatmap sorted by their PC scores from PCA of filtered integrated/scaled datasets" doc: | Genes per cells expression heatmap sorted by their PC scores from PCA of filtered integrated/scaled datasets. PDF format ntgr_pca_loadings_plot_png: type: File? outputSource: seurat_cluster/ntgr_pca_loadings_plot_png label: "PC scores of the most variant genes from PCA of filtered integrated/scaled datasets" doc: | PC scores of the most variant genes from PCA of filtered integrated/scaled datasets. PNG format 'sd:visualPlugins': - image: tab: 'Dimensionality evaluation' Caption: 'PC scores of the most variant genes from PCA of filtered integrated/scaled datasets' ntgr_pca_loadings_plot_pdf: type: File? outputSource: seurat_cluster/ntgr_pca_loadings_plot_pdf label: "PC scores of the most variant genes from PCA of filtered integrated/scaled datasets" doc: | PC scores of the most variant genes from PCA of filtered integrated/scaled datasets. PDF format ntgr_umap_spl_by_idnt_plot_png: type: File? outputSource: seurat_cluster/ntgr_umap_spl_by_idnt_plot_png label: "Split by identity UMAP projected PCA of filtered integrated/scaled datasets" doc: | Split by identity UMAP projected PCA of filtered integrated/scaled datasets. PNG format 'sd:visualPlugins': - image: tab: 'QC (integrated/scaled)' Caption: 'Split by identity UMAP projected PCA of filtered integrated/scaled datasets' ntgr_umap_spl_by_idnt_plot_pdf: type: File? outputSource: seurat_cluster/ntgr_umap_spl_by_idnt_plot_pdf label: "Split by identity UMAP projected PCA of filtered integrated/scaled datasets" doc: | Split by identity UMAP projected PCA of filtered integrated/scaled datasets. PDF format clst_umap_res_plot_png: type: - "null" - type: array items: File outputSource: seurat_cluster/clst_umap_res_plot_png label: "Clustered UMAP projected PCA of filtered integrated/scaled datasets" doc: | Clustered UMAP projected PCA of filtered integrated/scaled datasets. PNG format 'sd:visualPlugins': - image: tab: 'Clustering' Caption: 'Clustered UMAP projected PCA of filtered integrated/scaled datasets' clst_umap_res_plot_pdf: type: - "null" - type: array items: File outputSource: seurat_cluster/clst_umap_res_plot_pdf label: "Clustered UMAP projected PCA of filtered integrated/scaled datasets" doc: | Clustered UMAP projected PCA of filtered integrated/scaled datasets. PDF format clst_umap_spl_by_cond_res_plot_png: type: - "null" - type: array items: File outputSource: seurat_cluster/clst_umap_spl_by_cond_res_plot_png label: "Split by condition clustered UMAP projected PCA of filtered integrated/scaled datasets" doc: | Split by condition clustered UMAP projected PCA of filtered integrated/scaled datasets. PNG format 'sd:visualPlugins': - image: tab: 'Clustering' Caption: 'Split by condition clustered UMAP projected PCA of filtered integrated/scaled datasets' clst_umap_spl_by_cond_res_plot_pdf: type: - "null" - type: array items: File outputSource: seurat_cluster/clst_umap_spl_by_cond_res_plot_pdf label: "Split by condition clustered UMAP projected PCA of filtered integrated/scaled datasets" doc: | Split by condition clustered UMAP projected PCA of filtered integrated/scaled datasets. PDF format clst_umap_ctype_res_plot_png: type: - "null" - type: array items: File outputSource: seurat_cluster/clst_umap_ctype_res_plot_png label: "Grouped by predicted cell types UMAP projected PCA of filtered integrated/scaled datasets" doc: | Grouped by predicted cell types UMAP projected PCA of filtered integrated/scaled datasets. PNG format 'sd:visualPlugins': - image: tab: 'Clustering' Caption: 'Grouped by predicted cell types UMAP projected PCA of filtered integrated/scaled datasets' clst_umap_ctype_res_plot_pdf: type: - "null" - type: array items: File outputSource: seurat_cluster/clst_umap_ctype_res_plot_pdf label: "Grouped by predicted cell types UMAP projected PCA of filtered integrated/scaled datasets" doc: | Grouped by predicted cell types UMAP projected PCA of filtered integrated/scaled datasets. PDF format clst_umap_spl_by_ph_res_plot_png: type: - "null" - type: array items: File outputSource: seurat_cluster/clst_umap_spl_by_ph_res_plot_png label: "Split by cell cycle phase clustered UMAP projected PCA of filtered integrated/scaled datasets" doc: | Split by cell cycle phase clustered UMAP projected PCA of filtered integrated/scaled datasets. PNG format 'sd:visualPlugins': - image: tab: 'QC (integrated/scaled)' Caption: 'Split by cell cycle phase clustered UMAP projected PCA of filtered integrated/scaled datasets' clst_umap_spl_by_ph_res_plot_pdf: type: - "null" - type: array items: File outputSource: seurat_cluster/clst_umap_spl_by_ph_res_plot_pdf label: "Split by cell cycle phase clustered UMAP projected PCA of filtered integrated/scaled datasets" doc: | Split by cell cycle phase clustered UMAP projected PCA of filtered integrated/scaled datasets. PDF format clst_qc_mtrcs_res_plot_png: type: - "null" - type: array items: File outputSource: seurat_cluster/clst_qc_mtrcs_res_plot_png label: "QC metrics for clustered UMAP projected PCA of filtered integrated/scaled datasets" doc: | QC metrics for clustered UMAP projected PCA of filtered integrated/scaled datasets. PNG format 'sd:visualPlugins': - image: tab: 'QC (integrated/scaled)' Caption: 'QC metrics for clustered UMAP projected PCA of filtered integrated/scaled datasets' clst_qc_mtrcs_res_plot_pdf: type: - "null" - type: array items: File outputSource: seurat_cluster/clst_qc_mtrcs_res_plot_pdf label: "QC metrics for clustered UMAP projected PCA of filtered integrated/scaled datasets" doc: | QC metrics for clustered UMAP projected PCA of filtered integrated/scaled datasets. PDF format expr_avg_per_clst_res_plot_png: type: - "null" - type: array items: File outputSource: seurat_cluster/expr_avg_per_clst_res_plot_png label: "Scaled average log normalized gene expression per cluster of filtered integrated/scaled datasets" doc: | Scaled average log normalized gene expression per cluster of filtered integrated/scaled datasets. PNG format 'sd:visualPlugins': - image: tab: 'Gene expression' Caption: 'Scaled average log normalized gene expression per cluster of filtered integrated/scaled datasets' expr_avg_per_clst_res_plot_pdf: type: - "null" - type: array items: File outputSource: seurat_cluster/expr_avg_per_clst_res_plot_pdf label: "Scaled average log normalized gene expression per cluster of filtered integrated/scaled datasets" doc: | Scaled average log normalized gene expression per cluster of filtered integrated/scaled datasets. PDF format expr_per_clst_cell_res_plot_png: type: - "null" - type: array items: File outputSource: seurat_cluster/expr_per_clst_cell_res_plot_png label: "Log normalized gene expression per cell of clustered filtered integrated/scaled datasets" doc: | Log normalized gene expression per cell of clustered filtered integrated/scaled datasets. PNG format 'sd:visualPlugins': - image: tab: 'Gene expression' Caption: 'Log normalized gene expression per cell of clustered filtered integrated/scaled datasets' expr_per_clst_cell_res_plot_pdf: type: - "null" - type: array items: File outputSource: seurat_cluster/expr_per_clst_cell_res_plot_pdf label: "Log normalized gene expression per cell of clustered filtered integrated/scaled datasets" doc: | Log normalized gene expression per cell of clustered filtered integrated/scaled datasets. PDF format expr_clst_heatmap_res_plot_png: type: - "null" - type: array items: File outputSource: seurat_cluster/expr_clst_heatmap_res_plot_png label: "Log normalized gene expression heatmap of clustered filtered integrated/scaled datasets" doc: | Log normalized gene expression heatmap of clustered filtered integrated/scaled datasets. PNG format 'sd:visualPlugins': - image: tab: 'Gene expression' Caption: 'Log normalized gene expression heatmap of clustered filtered integrated/scaled datasets' expr_clst_heatmap_res_plot_pdf: type: - "null" - type: array items: File outputSource: seurat_cluster/expr_clst_heatmap_res_plot_pdf label: "Log normalized gene expression heatmap of clustered filtered integrated/scaled datasets" doc: | Log normalized gene expression heatmap of clustered filtered integrated/scaled datasets. PDF format expr_dnst_per_clst_res_plot_png: type: - "null" - type: array items: File outputSource: seurat_cluster/expr_dnst_per_clst_res_plot_png label: "Log normalized gene expression densities per cluster of filtered integrated/scaled datasets" doc: | Log normalized gene expression densities per cluster of filtered integrated/scaled datasets. PNG format 'sd:visualPlugins': - image: tab: 'Gene expression' Caption: 'Log normalized gene expression densities per cluster of filtered integrated/scaled datasets' expr_dnst_per_clst_res_plot_pdf: type: - "null" - type: array items: File outputSource: seurat_cluster/expr_dnst_per_clst_res_plot_pdf label: "Log normalized gene expression densities per cluster of filtered integrated/scaled datasets" doc: | Log normalized gene expression densities per cluster of filtered integrated/scaled datasets. PDF format expr_avg_per_ctype_res_plot_png: type: - "null" - type: array items: File outputSource: seurat_cluster/expr_avg_per_ctype_res_plot_png label: "Scaled average log normalized gene expression per predicted cell type of filtered integrated/scaled datasets" doc: | Scaled average log normalized gene expression per predicted cell type of filtered integrated/scaled datasets. PNG format 'sd:visualPlugins': - image: tab: 'Gene expression' Caption: 'Scaled average log normalized gene expression per predicted cell type of filtered integrated/scaled datasets' expr_avg_per_ctype_res_plot_pdf: type: - "null" - type: array items: File outputSource: seurat_cluster/expr_avg_per_ctype_res_plot_pdf label: "Scaled average log normalized gene expression per predicted cell type of filtered integrated/scaled datasets" doc: | Scaled average log normalized gene expression per predicted cell type of filtered integrated/scaled datasets. PDF format expr_per_ctype_cell_res_plot_png: type: - "null" - type: array items: File outputSource: seurat_cluster/expr_per_ctype_cell_res_plot_png label: "Log normalized gene expression per cell of clustered filtered integrated/scaled datasets with predicted cell types" doc: | Log normalized gene expression per cell of clustered filtered/scaled integrated datasets with predicted cell types. PNG format 'sd:visualPlugins': - image: tab: 'Gene expression' Caption: 'Log normalized gene expression per cell of clustered filtered/scaled integrated datasets with predicted cell types' expr_per_ctype_cell_res_plot_pdf: type: - "null" - type: array items: File outputSource: seurat_cluster/expr_per_ctype_cell_res_plot_pdf label: "Log normalized gene expression per cell of clustered filtered integrated/scaled datasets with predicted cell types" doc: | Log normalized gene expression per cell of clustered filtered integrated/scaled datasets with predicted cell types. PDF format expr_ctype_heatmap_res_plot_png: type: - "null" - type: array items: File outputSource: seurat_cluster/expr_ctype_heatmap_res_plot_png label: "Log normalized gene expression heatmap of clustered filtered integrated/scaled datasets with predicted cell types" doc: | Log normalized gene expression heatmap of clustered filtered integrated/scaled datasets with predicted cell types. PNG format 'sd:visualPlugins': - image: tab: 'Gene expression' Caption: 'Log normalized gene expression heatmap of clustered filtered integrated/scaled datasets with predicted cell types' expr_ctype_heatmap_res_plot_pdf: type: - "null" - type: array items: File outputSource: seurat_cluster/expr_ctype_heatmap_res_plot_pdf label: "Log normalized gene expression heatmap of clustered filtered integrated/scaled datasets with predicted cell types" doc: | Log normalized gene expression heatmap of clustered filtered integrated/scaled datasets with predicted cell types. PDF format expr_dnst_per_ctype_res_plot_png: type: - "null" - type: array items: File outputSource: seurat_cluster/expr_dnst_per_ctype_res_plot_png label: "Log normalized gene expression densities per predicted cell type of filtered integrated/scaled datasets" doc: | Log normalized gene expression densities per predicted cell type of filtered integrated/scaled datasets. PNG format 'sd:visualPlugins': - image: tab: 'Gene expression' Caption: 'Log normalized gene expression densities per predicted cell type of filtered integrated/scaled datasets' expr_dnst_per_ctype_res_plot_pdf: type: - "null" - type: array items: File outputSource: seurat_cluster/expr_dnst_per_ctype_res_plot_pdf label: "Log normalized gene expression densities per predicted cell type of filtered integrated/scaled datasets" doc: | Log normalized gene expression densities per predicted cell type of filtered integrated/scaled datasets. PDF format seurat_clst_data_rds: type: File outputSource: seurat_cluster/seurat_clst_data_rds label: "Clustered filtered integrated/scaled Seurat data" doc: | Clustered filtered integrated Seurat data. RDS format clst_pttv_gene_markers: type: File outputSource: seurat_cluster/clst_pttv_gene_markers label: "Putative gene markers file for all clusters and all resolutions" doc: | Putative gene markers file for all clusters and all resolutions. TSV format 'sd:visualPlugins': - syncfusiongrid: tab: 'Putative gene markers' Title: 'Putative gene markers' clst_csrvd_gene_markers: type: File outputSource: seurat_cluster/clst_csrvd_gene_markers label: "Conserved gene markers file for all clusters and all resolutions" doc: | Conserved gene markers file for all clusters and all resolutions. TSV format 'sd:visualPlugins': - syncfusiongrid: tab: 'Conserved gene markers' Title: 'Conserved gene markers' compressed_cellbrowser_config_data: type: File outputSource: compress_cellbrowser_config_data/compressed_folder label: "Compressed directory with UCSC Cellbrowser configuration data" doc: | Compressed directory with UCSC Cellbrowser configuration data cellbrowser_html_data: type: Directory outputSource: seurat_cluster/cellbrowser_html_data label: "Directory with UCSC Cellbrowser formatted html data" doc: | Directory with UCSC Cellbrowser formatted html data cellbrowser_html_file: type: File outputSource: seurat_cluster/cellbrowser_html_file label: "Open in UCSC Cell Browser" doc: | HTML index file from the directory with UCSC Cellbrowser formatted html data 'sd:visualPlugins': - linkList: tab: 'Overview' target: "_blank" seurat_cluster_stdout_log: type: File outputSource: seurat_cluster/stdout_log label: stdout log generated by Seurat doc: | stdout log generated by Seurat seurat_cluster_stderr_log: type: File outputSource: seurat_cluster/stderr_log label: stderr log generated by Seurat doc: | stderr log generated by Seurat steps: uncompress_feature_bc_matrices: in: compressed: filtered_feature_bc_matrix_folder out: - uncompressed run: cwlVersion: v1.0 class: CommandLineTool hints: - class: DockerRequirement dockerPull: biowardrobe2/scidap:v0.0.3 inputs: compressed: type: File inputBinding: position: 1 outputs: uncompressed: type: Directory outputBinding: glob: "*" baseCommand: ["tar", "xzf"] seurat_cluster: run: ../tools/seurat-cluster.cwl in: feature_bc_matrices_folder: uncompress_feature_bc_matrices/uncompressed aggregation_metadata: aggregation_metadata cell_cycle_data: cell_cycle_data conditions_data: conditions_data classifier_rds: classifier_rds species: species barcodes_data: barcodes_data minimum_cells: minimum_cells minimum_features: source: minimum_features valueFrom: $(split_numbers(self)) maximum_features: source: maximum_features valueFrom: $(split_numbers(self)) selected_features: source: selected_features valueFrom: $(split_features(self)) minimum_umis: source: minimum_umis valueFrom: $(split_numbers(self)) minimum_novelty_score: source: minimum_novelty_score valueFrom: $(split_numbers(self)) maximum_mito_perc: maximum_mito_perc mito_pattern: mito_pattern regress_cellcycle: regress_cellcycle regress_mito_perc: regress_mito_perc high_var_features_count: high_var_features_count dimensionality: dimensionality umap_spread: umap_spread umap_mindist: umap_mindist umap_nneighbors: umap_nneighbors umap_metric: umap_metric umap_method: umap_method no_sct: no_sct cluster_metric: cluster_metric resolution: source: resolution valueFrom: $(split_numbers(self)) minimum_logfc: minimum_logfc minimum_pct: minimum_pct only_positive_markers: only_positive_markers test_use: test_use export_pdf_plots: default: true export_rds_data: default: true threads: threads out: - raw_cell_count_plot_png - raw_cell_count_plot_pdf - raw_umi_dnst_spl_by_cond_plot_png - raw_umi_dnst_spl_by_cond_plot_pdf - raw_gene_dnst_spl_by_cond_plot_png - raw_gene_dnst_spl_by_cond_plot_pdf - raw_gene_umi_corr_spl_by_ident_plot_png - raw_gene_umi_corr_spl_by_ident_plot_pdf - raw_mito_perc_dnst_spl_by_cond_plot_png - raw_mito_perc_dnst_spl_by_cond_plot_pdf - raw_nvlt_score_dnst_spl_by_cond_plot_png - raw_nvlt_score_dnst_spl_by_cond_plot_pdf - raw_qc_mtrcs_plot_png - raw_qc_mtrcs_plot_pdf - raw_qc_mtrcs_gr_by_cond_plot_png - raw_qc_mtrcs_gr_by_cond_plot_pdf - fltr_cell_count_plot_png - fltr_cell_count_plot_pdf - fltr_umi_dnst_spl_by_cond_plot_png - fltr_umi_dnst_spl_by_cond_plot_pdf - fltr_gene_dnst_spl_by_cond_plot_png - fltr_gene_dnst_spl_by_cond_plot_pdf - fltr_gene_umi_corr_spl_by_ident_plot_png - fltr_gene_umi_corr_spl_by_ident_plot_pdf - fltr_mito_perc_dnst_spl_by_cond_plot_png - fltr_mito_perc_dnst_spl_by_cond_plot_pdf - fltr_nvlt_score_dnst_spl_by_cond_plot_png - fltr_nvlt_score_dnst_spl_by_cond_plot_pdf - fltr_qc_mtrcs_plot_png - fltr_qc_mtrcs_plot_pdf - fltr_qc_mtrcs_gr_by_cond_plot_png - fltr_qc_mtrcs_gr_by_cond_plot_pdf - fltr_pca_spl_by_ph_plot_png - fltr_pca_spl_by_ph_plot_pdf - fltr_pca_spl_by_mito_perc_plot_png - fltr_pca_spl_by_mito_perc_plot_pdf - fltr_umap_spl_by_idnt_plot_png - fltr_umap_spl_by_idnt_plot_pdf - ntgr_elbow_plot_png - ntgr_elbow_plot_pdf - ntgr_pca_plot_png - ntgr_pca_plot_pdf - ntgr_pca_heatmap_png - ntgr_pca_heatmap_pdf - ntgr_pca_loadings_plot_png - ntgr_pca_loadings_plot_pdf - ntgr_umap_spl_by_idnt_plot_png - ntgr_umap_spl_by_idnt_plot_pdf - clst_umap_res_plot_png - clst_umap_res_plot_pdf - clst_umap_spl_by_cond_res_plot_png - clst_umap_spl_by_cond_res_plot_pdf - clst_umap_ctype_res_plot_png - clst_umap_ctype_res_plot_pdf - clst_umap_spl_by_ph_res_plot_png - clst_umap_spl_by_ph_res_plot_pdf - clst_qc_mtrcs_res_plot_png - clst_qc_mtrcs_res_plot_pdf - clst_pttv_gene_markers - clst_csrvd_gene_markers - expr_avg_per_clst_res_plot_png - expr_avg_per_clst_res_plot_pdf - expr_per_clst_cell_res_plot_png - expr_per_clst_cell_res_plot_pdf - expr_clst_heatmap_res_plot_png - expr_clst_heatmap_res_plot_pdf - expr_dnst_per_clst_res_plot_png - expr_dnst_per_clst_res_plot_pdf - expr_avg_per_ctype_res_plot_png - expr_avg_per_ctype_res_plot_pdf - expr_per_ctype_cell_res_plot_png - expr_per_ctype_cell_res_plot_pdf - expr_ctype_heatmap_res_plot_png - expr_ctype_heatmap_res_plot_pdf - expr_dnst_per_ctype_res_plot_png - expr_dnst_per_ctype_res_plot_pdf - seurat_clst_data_rds - cellbrowser_config_data - cellbrowser_html_data - cellbrowser_html_file - stdout_log - stderr_log compress_cellbrowser_config_data: run: ../tools/tar-compress.cwl in: folder_to_compress: seurat_cluster/cellbrowser_config_data out: - compressed_folder $namespaces: s: http://schema.org/ $schemas: - https://github.com/schemaorg/schemaorg/raw/main/data/releases/11.01/schemaorg-current-http.rdf s:name: "Seurat Cluster" label: "Seurat Cluster" s:alternateName: "Runs filtering, integration, and clustering analyses for Cell Ranger Count Gene Expression or Cell Ranger Aggregate experiments" s:downloadUrl: https://raw.githubusercontent.com/datirium/workflows/master/workflows/seurat-cluster.cwl s:codeRepository: https://github.com/datirium/workflows s:license: http://www.apache.org/licenses/LICENSE-2.0 s:isPartOf: class: s:CreativeWork s:name: Common Workflow Language s:url: http://commonwl.org/ s:creator: - class: s:Organization s:legalName: "Cincinnati Children's Hospital Medical Center" s:location: - class: s:PostalAddress s:addressCountry: "USA" s:addressLocality: "Cincinnati" s:addressRegion: "OH" s:postalCode: "45229" s:streetAddress: "3333 Burnet Ave" s:telephone: "+1(513)636-4200" s:logo: "https://www.cincinnatichildrens.org/-/media/cincinnati%20childrens/global%20shared/childrens-logo-new.png" s:department: - class: s:Organization s:legalName: "Allergy and Immunology" s:department: - class: s:Organization s:legalName: "Barski Research Lab" s:member: - class: s:Person s:name: Michael Kotliar s:email: mailto:misha.kotliar@gmail.com s:sameAs: - id: http://orcid.org/0000-0002-6486-3898 doc: | Seurat Cluster ============== Runs filtering, integration, and clustering analyses for Cell Ranger Count Gene Expression or Cell Ranger Aggregate experiments.