import os import json from snakemake.utils import min_version min_version("6.6.1") configfile: "config/config.yaml" superregion_map = {} for s, v in config["superregions"].items(): for r in v: superregion_map[r] = s samples = [] groups = {} groups_unisex = {} donor_data = {} supergroups = {} sample_to_group = {} with open("config/samples.tsv") as sample_file: h = sample_file.readline().rstrip('\n').split('\t') series_ind = h.index("Series") region_ind = h.index("Region") status_ind = h.index("Status") sex_ind = h.index("Sex") donor_ind = h.index("Donor") samples = [] for line in sample_file: if line.startswith("#"): continue entries = line.rstrip('\n').split('\t') series = entries[series_ind] region = entries[region_ind] status = entries[status_ind] sex = entries[sex_ind] donor = entries[donor_ind] group_name = f"{region}-{status}-{sex}" samples.append(series) groups.setdefault(group_name, []).append(series) groups_unisex.setdefault(f"{region}-{status}", []).append(series) donor_data[series] = donor sample_to_group[series] = group_name supergroup_name = superregion_map[region] supergroups.setdefault(supergroup_name, set()).add(group_name) supergroups = {k: list(v) for k, v in supergroups.items()} group_to_supergroup = {} for k, v in supergroups.items(): for g in v: group_to_supergroup[g] = k group_names = list(groups.keys()) group_unisex_names = list(groups_unisex.keys()) supergroup_names = list(supergroups.keys()) hic_regions = set(config["hic_regions"]) hic_labels = config["hic_labels"] groups_hic = {} groups_unisex_hic = {} hic_files = {} with open("config/hic_samples.tsv") as sample_file: h = sample_file.readline().rstrip('\n').split('\t') exp_ind = h.index("Experiment") region_ind = h.index("Region") status_ind = h.index("Status") sex_ind = h.index("Sex") file_ind = h.index("File") samples = [] for line in sample_file: if line.startswith("#"): continue entries = line.rstrip('\n').split('\t') experiment = entries[exp_ind] region = entries[region_ind] # print(region) #### if region not in hic_regions: # print(region) #### continue status = entries[status_ind] sex = entries[sex_ind] file = entries[file_ind] group_name = f"{region}-{status}-{sex}" groups_hic.setdefault(group_name, []).append(experiment) groups_unisex_hic.setdefault(f"{region}-{status}", []).append(experiment) hic_files[experiment] = file group_unisex_names_hic = list(groups_unisex_hic.keys()) as_regions = set(config["as_regions"]) as_labels = config["as_labels"] donor_to_wgs_dir = {} with open("config/wgs_samples.tsv") as sample_file: h = sample_file.readline().rstrip('\n').split('\t') donor_ind = h.index("Donor") dir_ind = h.index("Directory") for line in sample_file: if line.startswith("#"): continue entries = line.rstrip('\n').split('\t') donor = entries[donor_ind] wdir = entries[dir_ind] donor_to_wgs_dir[donor] = wdir groups_wgs = {} for k, v in groups.items(): region = k.split("-")[0] if region not in as_regions: continue for s in v: donor = donor_data[s] if donor in donor_to_wgs_dir: wgs_dir = donor_to_wgs_dir[donor] groups_wgs.setdefault(k, []).append((wgs_dir, s),) groups_unisex_wgs = {} for k, v in groups_unisex.items(): region = k.split("-")[0] if region not in as_regions: continue for s in v: donor = donor_data[s] if donor in donor_to_wgs_dir: wgs_dir = donor_to_wgs_dir[donor] groups_unisex_wgs.setdefault(k, []).append((wgs_dir, s),) group_unisex_names_wgs = list(groups_unisex_wgs.keys()) # subcluster_jobs = [] # with open(workflow.source_path("files/subcluster_jobs.txt")) as f: # for line in f: # subcluster_jobs.append(line.rstrip("\n")) # with open("config/rna_cluster_names.txt") as f: # rna_cluster_names = [] # for line in f: # rna_cluster_names.append(line.rstrip("\n")) workdir: config['workdir'] max_threads = config["max_threads_per_rule"] # def script_path(script_name): # return str(workflow.source_path(script_name)) include: "rules/atac.smk" include: "rules/rna.smk" include: "rules/reference.smk" include: "rules/rna_group.smk" include: "rules/rna_import_emb.smk" include: "rules/atac_group.smk" include: "rules/rna_name_group.smk" include: "rules/rna_subcluster_cleanup.smk" include: "rules/rna_name_subclusters.smk" include: "rules/rna_name_subclusters_refined.smk" include: "rules/rna_l1_labeled.smk" include: "rules/export.smk" include: "rules/diff_exp.smk" include: "rules/soupx.smk" include: "rules/abc.smk" include: "rules/allele_specific.smk" rule all: """ Generate all outputs (default) """ input: # expand("results_supergroups/{supergroup}/{label}/rna/seurat_name_subclusters_supergroup/proj.rds", supergroup=supergroup_names, label=config["supergroup_labels"]), # expand("results_supergroups/{supergroup}/{label}/rna/seurat_named_subcluster_markers_supergroup/markers.tsv", supergroup=supergroup_names, label=config["supergroup_labels"]), # expand("results_groups/{group}/rna/seurat_subclusters_supergroups_to_groups/proj.rds", group=group_names), # expand("results_groups/{group}/rna/seurat_named_cluster_markers_refined/markers.tsv", group=group_names), # expand("results_groups/{group}/rna/seurat_add_seq_emb/proj.rds", group=group_names), # expand("results_groups/{group}/rna/seurat_embed_all/proj.rds", group=group_names), # expand("results/{sample}/rna/seurat_soupx_filtered/proj.rds", group=group_names), rule allele_specific: """ Run allele-specific analysis """ input: expand("results_unisex/{group}/allele_specific/label/{label}/atac/rasqual_output.txt", group=group_unisex_names_wgs, label=as_labels) rule abc: """ Run ABC enhancer-gene linking """ input: expand("results_unisex/{group}/abc/{label}/neighborhoods/GeneList.txt", group=group_unisex_names_hic, label=hic_labels), [ f"results_unisex/{group}/abc/{label}/predictions/{experiment}/EnhancerPredictionsAllPutative.tsv.gz" for group in group_unisex_names if group in groups_unisex_hic for label in config["hic_labels"] for experiment in groups_unisex_hic[group] ] rule soupx: """ Run ambient RNA decontamination on filtered data """ input: expand("results/{sample}/rna/seurat_soupx_filtered/proj.rds", sample=samples), "qc_all/seurat_soupx_filtered.pdf", expand("results/{sample}/rna/seurat_soupx_filtered/adjusted_counts/counts_mat.mtx", sample=samples), rule export_l1: """ Export level-1 cell type data """ input: expand("export_l1/{group}/metadata.tsv.gz", group=group_names), expand("export_l1/{group}/datasets.txt", group=group_names), expand("export_l1/{group}/labels/cell_types_l1.tsv.gz", group=group_names), expand("export_l1/{group}/markers", group=group_names), expand("export_l1/{group}/embeddings/rna_pca.tsv.gz", group=group_names), expand("export_l1/{group}/embeddings/rna_harmony.tsv.gz", group=group_names), expand("export_l1/{group}/embeddings/rna_umap.tsv.gz", group=group_names), expand("export_l1/{group}/embeddings/atac_lsi.tsv.gz", group=group_names), expand("export_l1/{group}/embeddings/atac_harmony.tsv.gz", group=group_names), expand("export_l1/{group}/embeddings/atac_umap.tsv.gz", group=group_names), expand("export_l1/{group}/figures.tar.gz", group=group_names), # rule subcluster_naming: # """ # Subcluster naming (pre-supergroup-refinement) # """ # input: # expand("results_subcluster_unified/{label}/rna/seurat_name_subclusters/proj.rds", label=config["l1_labels"]), # expand("results_subcluster_unified/{label}/rna/seurat_named_subcluster_markers/markers.tsv", label=config["l1_labels"]), # expand("results_groups/{group}/rna/seurat_subclusters_to_groups/proj.rds", group=group_names), # expand("results_groups/{group}/rna/seurat_named_cluster_markers/markers.tsv", group=group_names), # expand("results_supergroups/{supergroup}/{label}/rna/seurat_subcluster_supergroup/proj.rds", supergroup=supergroup_names, label=config["supergroup_labels"]), # expand("results_supergroups/{supergroup}/{label}/rna/seurat_subcluster_supergroup/label_plots.pdf", supergroup=supergroup_names, label=config["supergroup_labels"]), # expand("results_supergroups/{supergroup}/{label}/rna/seurat_subcluster_supergroup/label_plots.pdf", supergroup=supergroup_names, label=config["supergroup_labels"]), # expand("results_supergroups/{supergroup}/{label}/rna/seurat_plot_subcluster_markers_supergroup/markers.tsv", supergroup=supergroup_names, label=config["supergroup_labels"]), # expand("results_supergroups/{supergroup}/{label}/rna/seurat_plot_subcluster_genes_supergroup/heatmap.pdf", supergroup=supergroup_names, label=config["supergroup_labels"]), rule diff_exp: """ Finalize level-1 labels """ input: expand("results_diff_exp/label/{label}/collate_pseudobulks/mat.tsv", label=config["l1_labels"]), expand("results_diff_exp/label/{label}/run_deseq/coefficients", label=config["l1_labels"]), expand("results_diff_exp/label/{label}/run_deseq_sva/coefficients", label=config["l1_labels"]), expand("results_diff_exp/label/{label}/run_deseq_lv/coefficients", label=config["l1_labels"]), expand("results_diff_exp/label/{label}/run_deseq_sva_lv/coefficients", label=config["l1_labels"]), rule l1_finalize: """ Finalize level-1 labels """ input: # expand("results_subcluster/{supergroup}/{label}/rna/seurat_subcluster_2/proj.rds", supergroup=supergroup_names, label=config["l1_labels"]), # expand("results_subcluster/{supergroup}/{label}/rna/seurat_subcluster_2/label_plots.pdf", supergroup=supergroup_names, label=config["l1_labels"]), # expand("results_subcluster/{supergroup}/{label}/rna/seurat_plot_subcluster_markers/dotplot.pdf", supergroup=supergroup_names, label=config["l1_labels"]), expand("results_subcluster_unified/{label}/rna/seurat_subcluster_cleanup/proj.rds", label=config["l1_labels"]), expand("results_subcluster_unified/{label}/rna/seurat_subcluster_2/proj.rds", label=config["l1_labels"]), expand("results_subcluster_unified/{label}/rna/seurat_subcluster_2/label_plots.pdf", label=config["l1_labels"]), expand("results_subcluster_unified/{label}/rna/seurat_plot_subcluster_markers/markers.tsv", label=config["l1_labels"]), expand("results_subcluster_unified/{label}/rna/seurat_plot_subcluster_genes/dotplot.pdf", label=config["l1_labels"]), expand("results_groups/{group}/rna/seurat_clusters_to_groups/proj.rds", group=group_names), expand("results_groups/{group}/rna/seurat_write_rna_all/metadata.tsv", group=group_names), expand("results_groups/{group}/rna/seurat_write_l1_markers/markers", group=group_names), rule name_1: """ Generate outputs dependent on first-level cluster naming """ input: expand("results_groups/{group}/rna/seurat_name_group_1/proj.rds", group=groups.keys()), expand("results_groups/{group}/rna/seurat_plot_genes/dotplot.pdf", group=groups.keys()), # expand("results_subcluster/{supergroup}/{label}/rna/seurat_subcluster_supergroup/proj.rds", supergroup=supergroup_names, label=config["l1_labels"]), # expand("results_subcluster/{supergroup}/{label}/rna/seurat_subcluster_supergroup/label_plots.pdf", supergroup=supergroup_names, label=config["l1_labels"]), expand("results_subcluster_unified/{label}/rna/seurat_subcluster_unified/proj.rds", label=config["l1_labels"]), expand("results_subcluster_unified/{label}/rna/seurat_subcluster_unified/label_plots.pdf", label=config["l1_labels"]), expand("results_subcluster_unified/{label}/rna/seurat_integrate_subgroups_unified/umap_group_harmony.pdf", label=config["l1_labels"]), rule pre_name: # rule all: """ Generate all outputs prior to cluster naming """ input: # expand("results/{sample}/rna/seurat_transfer_rna/labels_kramann.tsv", sample=samples), # expand("results/{sample}/rna/seurat_transfer_rna/labels_teichmann.tsv", sample=samples), # expand("results/{sample}/rna/seurat_transfer_rna/labels_ellinor.tsv", sample=samples), # expand("results/{sample}/rna/seurat_transfer_rna/labels_azimuth.tsv", sample=samples), expand("results_groups/{group}/rna/seurat_integrate_rna/proj.rds", group=groups.keys()), expand("results_groups/{group}/rna/seurat_integrate_rna/integration_plots.pdf", group=groups.keys()), expand("results_groups/{group}/rna/seurat_cluster_rna/proj.rds", group=groups.keys()), expand("results_groups/{group}/rna/seurat_load_transfer_labels/reference_plots.pdf", group=groups.keys()), expand("results_groups/{group}/rna/seurat_embed_test/proj.rds", group=groups.keys()), expand("results_groups/{group}/rna/seurat_plot_cm/mats.pdf", group=groups.keys()), # expand("results_groups/{group}/atac/archr_embed", group=groups.keys()), # expand("results_groups/{group}/atac/archr_rna_clustering", group=groups.keys()), # expand("results_groups/{group}/rna/seurat_add_batch_data/proj.rds", group=groups.keys()), # expand("results_groups/{group}/rna/seurat_add_multiplexing_data/proj.rds", group=groups.keys()), # expand("results_groups/{group}/rna/seurat_plot_cluster_markers/dotplot.pdf", group=groups.keys()), # expand("results_groups/{group}/atac/archr_plot_genes/umaps", group=groups.keys()), # "results_merged/atac/archr_init", # "results_merged/atac/archr_label", # "export/atac/embeddings/harmony.tsv.gz", # "export/atac/embeddings/umap.tsv.gz", # "export/atac/labels/cell_types.tsv.gz", # "export/atac/markers", # "export/atac/metadata.tsv.gz", # "export/atac/figures.tar.gz", # "export/atac/datasets.txt", # "results_merged/rna/seurat_name_rna/proj.rds", # "export/rna/embeddings/harmony.tsv.gz", # "export/rna/embeddings/umap.tsv.gz", # "export/rna/labels/cell_types.tsv.gz", # "export/rna/markers", # "export/rna/metadata.tsv.gz", # "export/rna/figures.tar.gz", # "export/rna/datasets.txt" rule harmonize_seq_emb: """ Harmonize sequence embeddingså """ input: expand("results_groups/{group}/rna/seurat_add_seq_emb/proj.rds", group=groups.keys()), rule download_gtf: """ Download GTF data """ output: "results_merged/fetch/GRCh38.gtf.gz" params: url = config["gtf"] conda: "envs/fetch.yaml" shell: "curl --no-progress-meter -L {params.url} > {output}" def get_series(w): x = w.sample return x.split("-")[0] def get_replicate(w): x = w.sample return x.split("-")[1] rule get_dataset_info: """ Query ENCODE portal for dataset information """ output: "results/{sample}/fetch/dataset_info.json" params: series = get_series, replicate = 1, dcc_mode = config["dcc_mode"], dcc_api_key = os.environ.get("DCC_API_KEY"), dcc_secret_key = os.environ.get("DCC_SECRET_KEY") log: directory("logs/{sample}/get_dataset_info") conda: "envs/fetch.yaml" script: "scripts/get_dataset_info.py" rule query_fragments: """ Query ENCODE portal for fragments URL """ output: "results/{sample}/fetch/fragments_url.txt" params: series = get_series, replicate = 1, dcc_mode = config["dcc_mode"], dcc_api_key = os.environ.get("DCC_API_KEY"), dcc_secret_key = os.environ.get("DCC_SECRET_KEY") log: directory("logs/{sample}/query_fragments") conda: "envs/fetch.yaml" script: "scripts/get_fragments_url.py" rule download_fragments: """ Download fragments tarball """ input: "results/{sample}/fetch/fragments_url.txt" output: "results/{sample}/fetch/fragments.tar.gz" params: usr = os.environ.get("DCC_API_KEY"), pwd = os.environ.get("DCC_SECRET_KEY") conda: "envs/fetch.yaml" shell: "filename=$(basename -- \"$(< {input})\"); " "extension=\"${{filename##*.}}\"; " "fid=\"${{filename%%.*}}\"; " "alturl=\"https://www.encodeproject.org/files/${{fid}}/@@download/${{filename}}\"; " "echo $alturl; " #### "curl --no-progress-meter -L -f $(< {input}) > {output} || " "curl --no-progress-meter -L -f -u {params.usr}:{params.pwd} $(< {input}) > {output} || " "curl --no-progress-meter -L -f -u {params.usr}:{params.pwd} \"$alturl\" > {output} " rule extract_fragments: """ Extract fragments file from tarball """ input: "results/{sample}/fetch/fragments.tar.gz" output: directory("results/{sample}/fetch/fragments_extracted") conda: "envs/fetch.yaml" shell: "mkdir -p {output}; " "tar -xzf {input} --transform='s/.*\///' -C {output}" rule move_fragments: """ Move fragments data to final location """ input: "results/{sample}/fetch/fragments_extracted" output: frag = "results/{sample}/fetch/fragments.tsv.gz", frag_ind = "results/{sample}/fetch/fragments.tsv.gz.tbi" conda: "envs/fetch.yaml" shell: "cp {input}/fragments.tsv.gz {output.frag}; " "cp {input}/fragments.tsv.gz.tbi {output.frag_ind};" rule query_bam_atac: """ Query ENCODE portal for BAM """ output: "results/{sample}/fetch/bam_atac_url.txt" params: series = get_series, replicate = 1, dcc_mode = config["dcc_mode"], dcc_api_key = os.environ.get("DCC_API_KEY"), dcc_secret_key = os.environ.get("DCC_SECRET_KEY") log: directory("logs/{sample}/query_bam_atac") conda: "envs/fetch.yaml" script: "scripts/get_bam_atac_url.py" rule download_bam_atac: """ Download BAM """ input: "results/{sample}/fetch/bam_atac_url.txt" output: "results/{sample}/fetch/atac.bam" params: usr = os.environ.get("DCC_API_KEY"), pwd = os.environ.get("DCC_SECRET_KEY") conda: "envs/fetch.yaml" shell: "filename=$(basename -- \"$(< {input})\"); " "extension=\"${{filename##*.}}\"; " "fid=\"${{filename%%.*}}\"; " "alturl=\"https://www.encodeproject.org/files/${{fid}}/@@download/${{filename}}\"; " # "echo $alturl; " #### "curl --no-progress-meter -L -f $(< {input}) > {output} || " "curl --no-progress-meter -L -f -u {params.usr}:{params.pwd} $(< {input}) > {output} || " "curl --no-progress-meter -L -f -u {params.usr}:{params.pwd} \"$alturl\" > {output} " rule query_expression: """ Query ENCODE portal for gene expression matrix URL """ output: "results/{sample}/fetch/expression_url.txt" params: series = get_series, replicate = 1, dcc_mode = config["dcc_mode"], dcc_api_key = os.environ.get("DCC_API_KEY"), dcc_secret_key = os.environ.get("DCC_SECRET_KEY") log: directory("logs/{sample}/query_expression") conda: "envs/fetch.yaml" script: "scripts/get_expression_url.py" rule query_expression_raw: """ Query ENCODE portal for gene expression matrix URL """ output: "results/{sample}/fetch/expression_raw_url.txt" params: series = get_series, replicate = 1, dcc_mode = config["dcc_mode"], dcc_api_key = os.environ.get("DCC_API_KEY"), dcc_secret_key = os.environ.get("DCC_SECRET_KEY") log: directory("logs/{sample}/query_expression_raw") conda: "envs/fetch.yaml" script: "scripts/get_expression_raw_url.py" rule download_expression: """ Download expression tarball """ input: "results/{sample}/fetch/expression_url.txt" output: "results/{sample}/fetch/expression.tar.gz" params: usr = os.environ.get("DCC_API_KEY"), pwd = os.environ.get("DCC_SECRET_KEY") conda: "envs/fetch.yaml" shell: "filename=$(basename -- \"$(< {input})\"); " "extension=\"${{filename##*.}}\"; " "fid=\"${{filename%%.*}}\"; " "alturl=\"https://www.encodeproject.org/files/${{fid}}/@@download/${{filename}}\"; " "echo $alturl; " #### "curl --no-progress-meter -L -f $(< {input}) > {output} || " "curl --no-progress-meter -L -f -u {params.usr}:{params.pwd} $(< {input}) > {output} || " "curl --no-progress-meter -L -f -u {params.usr}:{params.pwd} \"$alturl\" > {output} " rule download_expression_raw: """ Download raw expression tarball """ input: "results/{sample}/fetch/expression_raw_url.txt" output: "results/{sample}/fetch/expression_raw.tar.gz" params: usr = os.environ.get("DCC_API_KEY"), pwd = os.environ.get("DCC_SECRET_KEY") conda: "envs/fetch.yaml" shell: "filename=$(basename -- \"$(< {input})\"); " "extension=\"${{filename##*.}}\"; " "fid=\"${{filename%%.*}}\"; " "alturl=\"https://www.encodeproject.org/files/${{fid}}/@@download/${{filename}}\"; " "echo $alturl; " #### "curl --no-progress-meter -L -f $(< {input}) > {output} || " "curl --no-progress-meter -L -f -u {params.usr}:{params.pwd} $(< {input}) > {output} || " "curl --no-progress-meter -L -f -u {params.usr}:{params.pwd} \"$alturl\" > {output} " rule extract_expression: """ Extract expression data from tarball """ input: "results/{sample}/fetch/expression.tar.gz" output: directory("results/{sample}/fetch/expression_extracted") conda: "envs/fetch.yaml" shell: "mkdir -p {output}; " "tar -xzf {input} --transform='s/.*\///' -C {output}" rule extract_expression_raw: """ Extract expression data from tarball """ input: "results/{sample}/fetch/expression_raw.tar.gz" output: directory("results/{sample}/fetch/expression_raw_extracted") conda: "envs/fetch.yaml" shell: "mkdir -p {output}; " "tar -xzf {input} --transform='s/.*\///' -C {output}" rule move_expression: """ Move expression data files to final location """ input: "results/{sample}/fetch/expression_extracted" output: matrix = "results/{sample}/fetch/matrix.mtx", features = "results/{sample}/fetch/features.tsv", barcodes = "results/{sample}/fetch/barcodes.tsv", conda: "envs/fetch.yaml" shell: "cp {input}/matrix.mtx {output.matrix}; " "cp {input}/features.tsv {output.features}; " "cp {input}/barcodes.tsv {output.barcodes};" rule move_expression_raw: """ Move expression data files to final location """ input: "results/{sample}/fetch/expression_raw_extracted" output: matrix = "results/{sample}/fetch/matrix_raw.mtx", features = "results/{sample}/fetch/features_raw.tsv", barcodes = "results/{sample}/fetch/barcodes_raw.tsv", conda: "envs/fetch.yaml" shell: "cp {input}/matrix.mtx {output.matrix}; " "cp {input}/features.tsv {output.features}; " "cp {input}/barcodes.tsv {output.barcodes};" rule download_kramann_data: """ Download reference data """ output: "reference/kramann/fetch/data.h5ad" params: url = config["rna_ref_kramann"]["unified"] conda: "envs/fetch.yaml" shell: "curl --no-progress-meter -L -f '{params.url}' > {output}" rule download_kramann_subcluster_data: """ Download reference subcluster data """ output: "reference/kramann/fetch/{subtype}/data.rds" params: url = lambda w: config["rna_ref_kramann"]["subtypes"][w.subtype] conda: "envs/fetch.yaml" shell: "curl --no-progress-meter -L -f '{params.url}' > {output}" rule download_ellinor_data: """ Download reference data """ output: mat = "reference/ellinor/fetch/matrix.mtx.gz", features = "reference/ellinor/fetch/features.tsv.gz", cells = "reference/ellinor/fetch/barcodes.tsv.gz", mat_raw = "reference/ellinor/fetch/matrix_raw.mtx.gz", features_raw = "reference/ellinor/fetch/features_raw.tsv.gz", cells_raw = "reference/ellinor/fetch/barcodes_raw.tsv.gz", metadata = "reference/ellinor/fetch/metadata.tsv.gz" params: url_mat = config["rna_ref_ellinor"]["mat"], url_features = config["rna_ref_ellinor"]["features"], url_cells = config["rna_ref_ellinor"]["cells"], url_mat_raw = config["rna_ref_ellinor"]["mat_raw"], url_features_raw = config["rna_ref_ellinor"]["features_raw"], url_cells_raw = config["rna_ref_ellinor"]["cells_raw"], url_metadata = config["rna_ref_ellinor"]["metadata"], conda: "envs/fetch.yaml" shell: "curl --no-progress-meter -L -f '{params.url_mat}' > {output.mat}; " "curl --no-progress-meter -L -f '{params.url_features}' > {output.features}; " "curl --no-progress-meter -L -f '{params.url_cells}' > {output.cells}; " "curl --no-progress-meter -L -f '{params.url_mat_raw}' > {output.mat_raw}; " "curl --no-progress-meter -L -f '{params.url_features_raw}' > {output.features_raw}; " "curl --no-progress-meter -L -f '{params.url_cells_raw}' > {output.cells_raw}; " "curl --no-progress-meter -L -f '{params.url_metadata}' > {output.metadata}; " rule download_teichmann_data: """ Download reference data """ output: "reference/teichmann/fetch/data.h5ad" params: url = config["rna_ref_teichmann_data"] conda: "envs/fetch.yaml" shell: "curl --no-progress-meter -L -f '{params.url}' > {output}" rule download_azimuth_data: """ Download reference data """ output: tarball = "reference/azimuth/heartref.SeuratData_1.0.0.tar.gz", data = directory("reference/azimuth/heartref") params: url = config["azimuth_ref"] conda: "envs/fetch.yaml" shell: "curl --no-progress-meter -L -f '{params.url}' > {output.tarball}; " "mkdir -p {output.data}; " "tar -xf {output.tarball} -C {output.data}" rule download_barcode_wl: """ Download barcode whitelist """ output: rna = "resources/whitelist_rna.txt", atac = "resources/whitelist_atac.txt" params: url_rna = config["bc_wl_rna"], url_atac = config["bc_wl_atac"], conda: "envs/fetch.yaml" shell: "curl --no-progress-meter -L -f '{params.url_rna}' | zcat -f > {output.rna}; " "curl --no-progress-meter -L -f '{params.url_atac}' | zcat -f > {output.atac}" rule download_archr_resources: """ Download genome data for ArchR """ output: bsgenome = "resources/bsgenome.tar.gz", anno = "resources/gene_annotation.rda" params: url_bsgenome = config["bsgenome"], url_anno = config["archr_gene_anno"], conda: "envs/fetch.yaml" shell: "curl --no-progress-meter -L -f '{params.url_bsgenome}' > {output.bsgenome}; " "curl --no-progress-meter -L -f '{params.url_anno}' > {output.anno}" rule download_chromsizes: """ Download chromsizes data """ output: sizes = "resources/GRCh38.chrom.sizes.tsv", chroms = "resources/GRCh38.chroms.tsv" params: url = config["chrom_sizes"] conda: "envs/fetch.yaml" shell: "curl --no-progress-meter -L -f '{params.url}' > {output.sizes}; " "awk '{{ print $1 }}' {output.sizes} > {output.chroms}" rule download_blacklist: """ Download genome blacklist """ output: "resources/blacklist.bed" params: url = config["blacklist"] conda: "envs/fetch.yaml" shell: "curl --no-progress-meter -L -f '{params.url}' | zcat -f > {output}" rule download_amulet_lowmem: """ Download AMULET utility """ output: directory("resources/amulet") params: repo = config["amulet_repo"] conda: "envs/fetch.yaml" shell: "git clone {params.repo} {output}" rule download_amulet: """ Download AMULET utility (low memory patch) """ output: directory("resources/amulet_lowmem") params: repo = config["amulet_repo_lowmem"] conda: "envs/fetch.yaml" shell: "git clone {params.repo} {output}"