example.yaml

username: arendeiro
email: arendeiro@cemm.oeaw.ac.at
website_root: http://biomedical-sequencing.at/bocklab/arendeiro/
supported_data_types:
  - ATAC-seq
  - ChIP-seq
  - RNA-seq
  - CNV
preferences:
  # For the next item, environment variables are formatted if they are of the form ${VAR}
  root_reference_dir: /home/${USER}/reference/
  root_projects_dir: /home/${USER}/projects/
  default_genome_assemblies:
    - human: hg38
    - mouse: mm10
  # The next item is the default computing configuration to use from divvy.
  # Run "divvy list" to see all options.
  # See more here: http://code.databio.org/divvy/
  computing_configuration: 'default'
  report:
    record_figures: True
    record_csv: True
    continuous_generation: True
    timestamp_figures: True
    timestamp_tables: True
  graphics:
    matplotlib:
      backend: TkAgg # Agg
      # key:values under rcParams are used to update matplotlib.rcParams
      rcParams:
        # this ensures text in plots is exported as text objects
        svg.fonttype: "none"
    seaborn:
      # key:values under parameters are passed to seaborn.set
      parameters:
        context: "paper"
        style: "white"
        palette: "colorblind"
        color_codes: True
    figure_saving:
      # these arguments are passed to matplotlib.pyplot.savefig
      # https://matplotlib.org/api/_as_gen/matplotlib.pyplot.savefig.html
      format: svg
      dpi: 300
      bbox_inches: "tight"
    close_saved_figures: True

sample_input_files:
  # values in this section can use string formatting
  # of the form {variable} to be completed with variables from the sample objects
  # Example:
  # ATAC-seq:
  #   aligned_filtered_bam:
  #     "{data_dir}/{sample_name}/mapped/{sample_name}.trimmed.bowtie2.filtered.bam"
  ATAC-seq:
    aligned_filtered_bam: "{data_dir}/{sample_name}/mapped/{sample_name}.trimmed.bowtie2.filtered.bam"
    peaks: "{data_dir}/{sample_name}/peaks/{sample_name}_peaks.narrowPeak"
    summits: "{data_dir}/{sample_name}/peaks/{sample_name}_summits.bed"
  ChIP-seq:
    aligned_filtered_bam: "{data_dir}/{sample_name}/mapped/{sample_name}.trimmed.bowtie2.filtered.bam"
  ChIPmentation:
    aligned_filtered_bam: "{data_dir}/{sample_name}/mapped/{sample_name}.trimmed.bowtie2.filtered.bam"
  CNV:
    log2_read_counts:
      1000kb: "{data_dir}/{sample_name}/{sample_name}_1000kb/CNAprofiles/log2_read_counts.igv"
      100kb: "{data_dir}/{sample_name}/{sample_name}_100kb/CNAprofiles/log2_read_counts.igv"
      10kb: "{data_dir}/{sample_name}/{sample_name}_10kb/CNAprofiles/log2_read_counts.igv"
  RNA-seq:
    aligned_filtered_bam: "{data_dir}/{sample_name}/mapped/{sample_name}.trimmed.bowtie2.filtered.bam"
    counts: "{data_dir}/{sample_name}/bowtie1_{genome}/bitSeq/{sample_name}.counts"

resources:
  lola:
    region_databases:
      # under each section, there should be a list of items
      hg19:
        - /home/${USER}/resources/regions/LOLACore/hg19/
        - /home/${USER}/resources/regions/customRegionDB/hg19/
      hg38:
        - /home/${USER}/resources/regions/LOLACore/hg38/
        - /home/${USER}/resources/regions/customRegionDB/hg38/
      mm10:
        - /home/${USER}/resources/regions/LOLACore/mm10/
        - /home/${USER}/resources/regions/customRegionDB/mm10/
    region_set_labeling_columns:
      - "collection"
      - "description"
      - "filename"
      - "cellType"
      - "tissue"
      - "antibody"
      - "treatment"
    output_column_names:
      odds_ratio: "oddsRatio"
      log_p_value: "pValueLog"
  meme:
    motif_databases:
      human: /home/${USER}/resources/motifs/motif_databases/HUMAN/HOCOMOCOv10.meme
      mouse: /home/${USER}/resources/motifs/motif_databases/MOUSE/uniprobe_mouse.meme
      vertebrate: /home/arendeiro/workspace/homer_4.8/data/knownTFs/vertebrates/known.motifs
    motif_id_mapping:
      mouse: /home/${USER}/resources/motifs/motif_databases/MOUSE/uniprobe_mouse.id_mapping.tsv
  enrichr:
    gene_set_libraries:
      # this should be a list of items
      - "GO_Biological_Process_2015"
      - "ChEA_2015"
      - "KEGG_2016"
      - "ESCAPE"
      - "Epigenomics_Roadmap_HM_ChIP-seq"
      - "ENCODE_TF_ChIP-seq_2015"
      - "ENCODE_and_ChEA_Consensus_TFs_from_ChIP-X"
      - "ENCODE_Histone_Modifications_2015"
      - "OMIM_Expanded"
      - "TF-LOF_Expression_from_GEO"
      - "Gene_Perturbations_from_GEO_down"
      - "Gene_Perturbations_from_GEO_up"
      - "Disease_Perturbations_from_GEO_down"
      - "Disease_Perturbations_from_GEO_up"
      - "Drug_Perturbations_from_GEO_down"
      - "Drug_Perturbations_from_GEO_up"
      - "WikiPathways_2016"
      - "Reactome_2016"
      - "BioCarta_2016"
      - "NCI-Nature_2016"
      - "BioPlanet_2019"

executables:
  twoBitToFa: twoBitToFa
  fasta-dinucleotide-shuffle: fasta-dinucleotide-shuffle
  ame: ame
  findMotifsGenome.pl: findMotifsGenome.pl
  compareMotifs.pl: compareMotifs.pl