name: "calculate_qc_metrics"
namespace: "qc"
version: "2.1.2"
authors:
- name: "Dries Schaumont"
  roles:
  - "author"
  info:
    role: "Core Team Member"
    links:
      email: "dries@data-intuitive.com"
      github: "DriesSchaumont"
      orcid: "0000-0002-4389-0440"
      linkedin: "dries-schaumont"
    organizations:
    - name: "Data Intuitive"
      href: "https://www.data-intuitive.com"
      role: "Data Scientist"
argument_groups:
- name: "Inputs"
  arguments:
  - type: "file"
    name: "--input"
    description: "Input h5mu file"
    info: null
    example:
    - "input.h5mu"
    must_exist: true
    create_parent: true
    required: true
    direction: "input"
    multiple: false
    multiple_sep: ";"
  - type: "string"
    name: "--modality"
    info: null
    default:
    - "rna"
    required: false
    direction: "input"
    multiple: false
    multiple_sep: ";"
  - type: "string"
    name: "--layer"
    info: null
    example:
    - "raw_counts"
    required: false
    direction: "input"
    multiple: false
    multiple_sep: ";"
- name: "Metrics added to .obs"
  arguments:
  - type: "string"
    name: "--var_qc_metrics"
    description: "Keys to select a boolean (containing only True or False) column\
      \ from .var.\nFor each cell, calculate the proportion of total values for genes\
      \ which are labeled 'True', \ncompared to the total sum of the values for all\
      \ genes.\n"
    info: null
    example:
    - "ercc,highly_variable,mitochondrial"
    required: false
    direction: "input"
    multiple: true
    multiple_sep: ";"
  - type: "boolean"
    name: "--var_qc_metrics_fill_na_value"
    description: "Fill any 'NA' values found in the columns specified with --var_qc_metrics\
      \ to 'True' or 'False'.\nas False.\n"
    info: null
    required: false
    direction: "input"
    multiple: false
    multiple_sep: ";"
  - type: "integer"
    name: "--top_n_vars"
    description: "Number of top vars to be used to calculate cumulative proportions.\n\
      If not specified, proportions are not calculated. `--top_n_vars 20;50` finds\n\
      cumulative proportion to the 20th and 50th most expressed vars.\n"
    info: null
    required: false
    direction: "input"
    multiple: true
    multiple_sep: ";"
  - type: "string"
    name: "--output_obs_num_nonzero_vars"
    description: "Name of column in .obs describing, for each observation, the number\
      \ of stored values\n(including explicit zeroes). In other words, the name of\
      \ the column that counts\nfor each row the number of columns that contain data.\n"
    info: null
    default:
    - "num_nonzero_vars"
    required: false
    direction: "input"
    multiple: false
    multiple_sep: ";"
  - type: "string"
    name: "--output_obs_total_counts_vars"
    description: "Name of the column for .obs describing, for each observation (row),\n\
      the sum of the stored values in the columns.\n"
    info: null
    default:
    - "total_counts"
    required: false
    direction: "input"
    multiple: false
    multiple_sep: ";"
- name: "Metrics added to .var"
  arguments:
  - type: "string"
    name: "--output_var_num_nonzero_obs"
    description: "Name of column describing, for each feature, the number of stored\
      \ values\n(including explicit zeroes). In other words, the name of the column\
      \ that counts\nfor each column the number of rows that contain data.\n"
    info: null
    default:
    - "num_nonzero_obs"
    required: false
    direction: "input"
    multiple: false
    multiple_sep: ";"
  - type: "string"
    name: "--output_var_total_counts_obs"
    description: "Name of the column in .var describing, for each feature (column),\n\
      the sum of the stored values in the rows.\n"
    info: null
    default:
    - "total_counts"
    required: false
    direction: "input"
    multiple: false
    multiple_sep: ";"
  - type: "string"
    name: "--output_var_obs_mean"
    description: "Name of the column in .obs providing the mean of the values in each\
      \ row.\n"
    info: null
    default:
    - "obs_mean"
    required: false
    direction: "input"
    multiple: false
    multiple_sep: ";"
  - type: "string"
    name: "--output_var_pct_dropout"
    description: "Name of the column in .obs providing for each feature the percentage\
      \ of\nobservations the feature does not appear on (i.e. is missing). Same as\
      \ `--num_nonzero_obs`\nbut percentage based.\n"
    info: null
    default:
    - "pct_dropout"
    required: false
    direction: "input"
    multiple: false
    multiple_sep: ";"
- name: "Outputs"
  arguments:
  - type: "file"
    name: "--output"
    description: "Output h5mu file."
    info: null
    example:
    - "output.h5mu"
    must_exist: true
    create_parent: true
    required: false
    direction: "output"
    multiple: false
    multiple_sep: ";"
  - type: "string"
    name: "--output_compression"
    description: "The compression format to be used on the output h5mu object."
    info: null
    example:
    - "gzip"
    required: false
    choices:
    - "gzip"
    - "lzf"
    direction: "input"
    multiple: false
    multiple_sep: ";"
resources:
- type: "python_script"
  path: "script.py"
  is_executable: true
- type: "file"
  path: "setup_logger.py"
- type: "file"
  path: "compress_h5mu.py"
- type: "file"
  path: "nextflow_labels.config"
  dest: "nextflow_labels.config"
description: "Add basic quality control metrics to an .h5mu file.\n\nThe metrics are\
  \ comparable to what scanpy.pp.calculate_qc_metrics output,\nalthough they have\
  \ slightly different names:\n\nVar metrics (name in this component -> name in scanpy):\n\
  \  - pct_dropout -> pct_dropout_by_{expr_type}\n  - num_nonzero_obs -> n_cells_by_{expr_type}\n\
  \  - obs_mean -> mean_{expr_type}\n  - total_counts -> total_{expr_type}\n\n  Obs\
  \ metrics:\n    - num_nonzero_vars -> n_genes_by_{expr_type}\n    - pct_{var_qc_metrics}\
  \ -> pct_{expr_type}_{qc_var}\n    - total_counts_{var_qc_metrics} -> total_{expr_type}_{qc_var}\n\
  \    - pct_of_counts_in_top_{top_n_vars}_vars -> pct_{expr_type}_in_top_{n}_{var_type}\n\
  \    - total_counts -> total_{expr_type}\n    \n"
test_resources:
- type: "python_script"
  path: "test.py"
  is_executable: true
- type: "file"
  path: "pbmc_1k_protein_v3_filtered_feature_bc_matrix.h5mu"
info: null
status: "enabled"
scope:
  image: "public"
  target: "public"
license: "MIT"
links:
  repository: "https://github.com/openpipelines-bio/openpipeline"
  docker_registry: "ghcr.io"
runners:
- type: "executable"
  id: "executable"
  docker_setup_strategy: "ifneedbepullelsecachedbuild"
- type: "nextflow"
  id: "nextflow"
  directives:
    label:
    - "singlecpu"
    - "midmem"
    tag: "$id"
  auto:
    simplifyInput: true
    simplifyOutput: false
    transcript: false
    publish: false
  config:
    labels:
      mem1gb: "memory = 1000000000.B"
      mem2gb: "memory = 2000000000.B"
      mem5gb: "memory = 5000000000.B"
      mem10gb: "memory = 10000000000.B"
      mem20gb: "memory = 20000000000.B"
      mem50gb: "memory = 50000000000.B"
      mem100gb: "memory = 100000000000.B"
      mem200gb: "memory = 200000000000.B"
      mem500gb: "memory = 500000000000.B"
      mem1tb: "memory = 1000000000000.B"
      mem2tb: "memory = 2000000000000.B"
      mem5tb: "memory = 5000000000000.B"
      mem10tb: "memory = 10000000000000.B"
      mem20tb: "memory = 20000000000000.B"
      mem50tb: "memory = 50000000000000.B"
      mem100tb: "memory = 100000000000000.B"
      mem200tb: "memory = 200000000000000.B"
      mem500tb: "memory = 500000000000000.B"
      mem1gib: "memory = 1073741824.B"
      mem2gib: "memory = 2147483648.B"
      mem4gib: "memory = 4294967296.B"
      mem8gib: "memory = 8589934592.B"
      mem16gib: "memory = 17179869184.B"
      mem32gib: "memory = 34359738368.B"
      mem64gib: "memory = 68719476736.B"
      mem128gib: "memory = 137438953472.B"
      mem256gib: "memory = 274877906944.B"
      mem512gib: "memory = 549755813888.B"
      mem1tib: "memory = 1099511627776.B"
      mem2tib: "memory = 2199023255552.B"
      mem4tib: "memory = 4398046511104.B"
      mem8tib: "memory = 8796093022208.B"
      mem16tib: "memory = 17592186044416.B"
      mem32tib: "memory = 35184372088832.B"
      mem64tib: "memory = 70368744177664.B"
      mem128tib: "memory = 140737488355328.B"
      mem256tib: "memory = 281474976710656.B"
      mem512tib: "memory = 562949953421312.B"
      cpu1: "cpus = 1"
      cpu2: "cpus = 2"
      cpu5: "cpus = 5"
      cpu10: "cpus = 10"
      cpu20: "cpus = 20"
      cpu50: "cpus = 50"
      cpu100: "cpus = 100"
      cpu200: "cpus = 200"
      cpu500: "cpus = 500"
      cpu1000: "cpus = 1000"
    script:
    - "includeConfig(\"nextflow_labels.config\")"
  debug: false
  container: "docker"
engines:
- type: "docker"
  id: "docker"
  image: "python:3.11-slim"
  target_tag: "2.1.0"
  namespace_separator: "/"
  setup:
  - type: "apt"
    packages:
    - "procps"
    interactive: false
  - type: "python"
    user: false
    packages:
    - "anndata~=0.11.1"
    - "mudata~=0.3.1"
    - "scipy"
    script:
    - "exec(\"try:\\n  import awkward\\nexcept ModuleNotFoundError:\\n  exit(0)\\\
      nelse:  exit(1)\")"
    upgrade: true
  test_setup:
  - type: "apt"
    packages:
    - "git"
    interactive: false
  - type: "python"
    user: false
    packages:
    - "viashpy==0.8.0"
    github:
    - "openpipelines-bio/core#subdirectory=packages/python/openpipeline_testutils"
    upgrade: true
  - type: "python"
    user: false
    packages:
    - "scanpy"
    upgrade: true
  entrypoint: []
  cmd: null
build_info:
  config: "src/qc/calculate_qc_metrics/config.vsh.yaml"
  runner: "nextflow"
  engine: "docker"
  output: "target/nextflow/qc/calculate_qc_metrics"
  executable: "target/nextflow/qc/calculate_qc_metrics/main.nf"
  viash_version: "0.9.4"
  git_commit: "a0c9522486585774f76416150f8a3291409b5363"
  git_remote: "https://github.com/openpipelines-bio/openpipeline"
  git_tag: "2.1.1-2-ga0c95224865"
package_config:
  name: "openpipeline"
  summary: "Best-practice workflows for single-cell multi-omics analyses.\n"
  description: "OpenPipelines are extensible single cell analysis pipelines for reproducible\
    \ and large-scale single cell processing using [Viash](https://viash.io) and [Nextflow](https://www.nextflow.io/).\n\
    \nIn terms of workflows, the following has been made available, but keep in mind\
    \ that\nindividual tools and functionality can be executed as standalone components\
    \ as well.\n\n  * Demultiplexing: conversion of raw sequencing data to FASTQ objects.\n\
    \  * Ingestion: Read mapping and generating a count matrix.\n  * Single sample\
    \ processing: cell filtering and doublet detection.\n  * Multisample processing:\
    \ Count transformation, normalization, QC metric calulations.\n  * Integration:\
    \ Clustering, integration and batch correction using single and multimodal methods.\n\
    \  * Downstream analysis workflows\n"
  info:
    test_resources:
    - type: "s3"
      path: "s3://openpipelines-data"
      dest: "resources_test"
  viash_version: "0.9.4"
  source: "src"
  target: "target"
  config_mods:
  - ".resources += {path: '/src/workflows/utils/labels.config', dest: 'nextflow_labels.config'}\n\
    .runners[.type == 'nextflow'].config.script := 'includeConfig(\"nextflow_labels.config\"\
    )'"
  - ".version := \"2.1.2\""
  - ".engines[.type == 'docker'].target_tag := '2.1.0'"
  keywords:
  - "single-cell"
  - "multimodal"
  license: "MIT"
  organization: "openpipelines-bio"
  links:
    repository: "https://github.com/openpipelines-bio/openpipeline"
    docker_registry: "ghcr.io"
    homepage: "https://openpipelines.bio"
    documentation: "https://openpipelines.bio/fundamentals"
    issue_tracker: "https://github.com/openpipelines-bio/openpipeline/issues"
