# This file created by conda-build 3.21.4
# meta.yaml template originally from:
# /opt/recipe, last modified Thu Jan  6 18:04:08 2022
# ------------------------------------------------

package:
  name: gcen
  version: 0.6.0
source:
  sha256: daccabbdc8bf03ed4013e05b3a03ad171d1f98b0649455af934cbe938068153f
  url: https://github.com/wen-chen/gcen/releases/download/v0.6.0/gcen-0.6.0-source.tar.gz
build:
  number: '0'
  string: h7d875b9_0
requirements:
  build:
    - _libgcc_mutex 0.1 conda_forge
    - _openmp_mutex 4.5 1_gnu
    - binutils_impl_linux-64 2.36.1 h193b22a_2
    - binutils_linux-64 2.36 hf3e587d_3
    - gcc_impl_linux-64 9.4.0 h03d3576_11
    - gcc_linux-64 9.4.0 h391b98a_3
    - gxx_impl_linux-64 9.4.0 h03d3576_11
    - gxx_linux-64 9.4.0 h0316aca_3
    - kernel-headers_linux-64 2.6.32 he073ed8_15
    - ld_impl_linux-64 2.36.1 hea4e1c9_2
    - libgcc-devel_linux-64 9.4.0 hd854feb_11
    - libgcc-ng 11.2.0 h1d223b6_11
    - libgomp 11.2.0 h1d223b6_11
    - libsanitizer 9.4.0 h79bfe98_11
    - libstdcxx-devel_linux-64 9.4.0 hd854feb_11
    - libstdcxx-ng 11.2.0 he4da1e4_11
    - make 4.3 hd18ef5c_1
    - sysroot_linux-64 2.12 he073ed8_15
  host:
    - _libgcc_mutex 0.1 conda_forge
    - _openmp_mutex 4.5 1_gnu
    - libgcc-ng 11.2.0 h1d223b6_11
    - libgomp 11.2.0 h1d223b6_11
    - libstdcxx-ng 11.2.0 he4da1e4_11
  run:
    - libgcc-ng >=9.4.0
    - libstdcxx-ng >=9.4.0
test:
  commands:
    - network_build -h
about:
  description: 'GCEN is a command-line toolkit that allows biologists to easily build
    gene co-expression network and predict gene function, especially in RNA-Seq research
    or lncRNAs annotation. GCEN is primarily designed to be used in lncRNAs annotation,
    but is not limited to those scenarios. It is an efficient and easy-to-use solution
    that will allow everyone to perform gene co-expression network analysis without
    sophisticated programming skills. The recommended pipeline consists of four parts:
    data pretreatment, network construction, module identification, and function annotation.
    A README file and sample data are included in the software package. Because of
    its modular design, the GCEN can be easily integrated into another pipeline. Also,
    the multithreaded implementation of GCEN makes it fast and efficient for RNA-Seq
    data.'
  home: https://www.biochen.org/gcen/
  license: GPL v3
  summary: An easy toolkit of Gene Co-Expression Network analysis for lncRNAs annotation
extra:
  copy_test_source_files: true
  final: true
  identifiers:
    - biotools:gcen
