definition.yml

method:
  id: oscope
  name: Oscope
  tool_id: oscope
  source: tool
  platform: R
  url: https://bioconductor.org/packages/release/bioc/html/Oscope.html
  license: Artistic-2.0
  authors:
  - given: Ning
    family: Leng
    email: lengning1@gmail.com
    ORCID: 0000-0003-3641-729X
    github: lengning

manuscript:
  doi: 10.1038/nmeth.3549
  google_scholar_cluster_id: '6169309172636415425'
  publication_date: '2015-08-24'

container:
  url: https://github.com/dynverse/ti_oscope
  docker: dynverse/ti_oscope

wrapper:
  type: cyclic_trajectory
  topology_inference: fixed
  trajectory_types: cycle
  input_required: counts

parameters:
  - id: alternative_median
    type: logical
    default: false
    description: |-
      If alternative = TRUE, the alternative version of median normalization will be applied.
      The alternative method is similar to median-by-ratio normalization, but can deal with
      the cases when all of the genes/isoforms have at least one zero counts (in which case
      the median-by-ratio normalization will fail).
  - id: filter_genes
    type: logical
    default: true
    description: |-
      Whether or not to filter the genes using the CalcMV function.
  - id: mean_cut
    description: |-
      It is suggested to apply Oscope on genes with high mean and high variance.
      By default, the lower boundary is specified as 100, consequently only genes
      with mean > 100 will be used. The CalcMV function will fit a linear regression
      on log(variance)~log(mean) on these genes. Genes with variance above this
      line are considered as the high mean high variance genes.
    type: integer_range
    default:
    - 100
    - 100000000
    lower_distribution:
      type: expuniform
      lower: 10
      upper: 100
    upper_distribution:
      type: expuniform
      lower: 100
      upper: 100000000
  - id: qt
    description: |-
      Thresholds for outlier adjustment. For each gene/isoform, values <= qt1 th
      quantile (>= qt2 th quantile) will be pushed to qt1 th quantile (qt2 th quantile)
      prior to the scaling. default values are 0.05 and 0.95.
    type: numeric_range
    default:
    - .05
    - .95
    lower_distribution:
      type: uniform
      lower: 0
      upper: 1
    upper_distribution:
      type: uniform
      lower: 0
      upper: 1
  - id: quan
    type: numeric
    default: .95
    distribution:
      type: uniform
      lower: 0
      upper: 1
    description: Only gene pairs with similarity score >= quan th quantile will be considered in the clustering analyses.
  - id: ndg
    type: integer
    default: 3
    distribution:
      type: uniform
      lower: 1
      upper: 10
    description: degree of polynomial.
  - id: nchun
    type: integer
    default: 4
    distribution:
      type: uniform
      lower: 1
      upper: 10
    description: number of starting points for polynomial fitting.
  - id: niter
    type: integer
    default: 20000
    distribution:
      type: expuniform
      lower: 1000
      upper: 1000000
    description: The 2-opt algorithm will stop if N iterations has been performed or if the optimal order
  - id: ncthre
    type: integer
    default: 1000
    distribution:
      type: expuniform
      lower: 100
      upper: 100000
    description: no description was found