{% set version = '1.1.0' %}

{% set posix = 'm2-' if win else '' %}
{% set native = 'm2w64-' if win else '' %}

package:
  name: r-diffee
  version: {{ version|replace("-", "_") }}

source:
  url:
    - {{ cran_mirror }}/src/contrib/diffee_{{ version }}.tar.gz
    - {{ cran_mirror }}/src/contrib/Archive/diffee/diffee_{{ version }}.tar.gz
  sha256: c2988496e3c929241c74552fa5bcefc978b726227d6b08ab7fbd82f3f30d8b06

build:
  merge_build_host: True  # [win]
  # If this is a new build for the same version, increment the build number.
  number: 0
  # no skip
  noarch: generic

  # This is required to make R link correctly on Linux.
  rpaths:
    - lib/R/lib/
    - lib/

requirements:
  build:
    - {{posix}}zip               # [win]

  host:
    - r-base
    - r-igraph
    - r-pcapp

  run:
    - r-base
    - r-igraph
    - r-pcapp

test:
  commands:
    # You can put additional test commands to be run here.
    - $R -e "library('diffee')"           # [not win]
    - "\"%R%\" -e \"library('diffee')\""  # [win]

  # You can also put a file called run_test.py, run_test.sh, or run_test.bat
  # in the recipe that will be run at test time.

  # requires:
    # Put any additional test requirements here.

about:
  home: https://github.com/QData/DIFFEE
  license: GPL-2
  summary: 'This is an R implementation of Fast and Scalable Learning of Sparse Changes in High-Dimensional
    Gaussian Graphical Model Structure (DIFFEE). The DIFFEE algorithm can be used to
    fast estimate the differential network between two related datasets. For instance,
    it can identify differential gene network from datasets of case and control. By
    performing data-driven network inference from two high-dimensional data sets, this
    tool can help users effectively translate two aggregated data blocks into knowledge
    of the changes among entities between two Gaussian Graphical Model. Please run demo(diffeeDemo)
    to learn the basic functions provided by this package. For further details, please
    read the original paper: Beilun Wang, Arshdeep Sekhon, Yanjun Qi (2018) <arXiv:1710.11223>.'

  license_family: GPL2
  license_file:
    - '{{ environ["PREFIX"] }}/lib/R/share/licenses/GPL-2'

extra:
  recipe-maintainers:
    - katietz

# The original CRAN metadata for this package was:

# Package: diffee
# Version: 1.1.0
# Date: 2018-07-03
# Title: Fast and Scalable Learning of Sparse Changes in High-Dimensional Gaussian Graphical Model Structure
# Authors@R: c(person("Beilun", "Wang", role = c("aut", "cre"), email = "bw4mw@virginia.edu"), person("Yanjun", "Qi", role = "aut", email = "yanjun@virginia.edu"),person("Zhaoyang", "Wang", role = c("aut"), email = "zw4dn@virginia.edu"))
# Author: Beilun Wang [aut, cre], Yanjun Qi [aut], Zhaoyang Wang [aut]
# Maintainer: Beilun Wang <bw4mw@virginia.edu>
# Depends: R (>= 3.0.0), igraph, pcaPP
# Description: This is an R implementation of Fast and Scalable Learning of Sparse Changes in High-Dimensional Gaussian Graphical Model Structure (DIFFEE). The DIFFEE algorithm can be used to fast estimate the differential network between two related datasets. For instance, it can identify differential gene network from datasets of case and control. By performing data-driven network inference from two high-dimensional data sets, this tool can help users effectively translate two aggregated data blocks into knowledge of the changes among entities between two Gaussian Graphical Model. Please run demo(diffeeDemo) to learn the basic functions provided by this package. For further details, please read the original paper: Beilun Wang, Arshdeep Sekhon, Yanjun Qi (2018) <arXiv:1710.11223>.
# License: GPL-2
# URL: https://github.com/QData/DIFFEE
# BugReports: https://github.com/QData/DIFFEE
# RoxygenNote: 6.0.1
# NeedsCompilation: no
# Packaged: 2018-07-03 19:28:20 UTC; Karen Chen
# Repository: CRAN
# Date/Publication: 2018-07-03 19:50:03 UTC

# See
# https://docs.conda.io/projects/conda-build for
# more information about meta.yaml
