# This file created by conda-build 3.15.1
# meta.yaml template originally from:
# /opt/recipe, last modified Wed Dec 19 07:24:31 2018
# ------------------------------------------------

package:
    name: bioconductor-biosigner
    version: 1.10.0
source:
    md5: 5a7f57cd3552ed1c2cf21cf18f33da77
    url:
        - https://bioarchive.galaxyproject.org/biosigner_1.10.0.tar.gz
        - https://bioconductor.org/packages/3.8/bioc/src/contrib/biosigner_1.10.0.tar.gz
        - https://depot.galaxyproject.org/software/bioconductor-biosigner/bioconductor-biosigner_1.10.0_src_all.tar.gz
build:
    noarch: generic
    number: '0'
    rpaths:
        - lib/
        - lib/R/lib/
    string: r351_0
requirements:
    host:
        - _r-mutex 1.0.0 anacondar_1
        - binutils_impl_linux-64 2.31.1 h6176602_1
        - binutils_linux-64 2.31.1 h6176602_3
        - bioconductor-biobase 2.42.0 r351h14c3975_0
        - bioconductor-biocgenerics 0.28.0 r351_1
        - bioconductor-ropls 1.14.0 r351_0
        - bwidget 1.9.11 1
        - bzip2 1.0.6 h14c3975_1002
        - ca-certificates 2018.10.15 ha4d7672_0
        - cairo 1.14.12 h80bd089_1005
        - curl 7.63.0 h646f8bb_1000
        - fontconfig 2.13.1 h2176d3f_1000
        - freetype 2.9.1 h3cfcefd_1004
        - gcc_impl_linux-64 7.3.0 habb00fd_1
        - gcc_linux-64 7.3.0 h553295d_3
        - gettext 0.19.8.1 h9745a5d_1001
        - gfortran_impl_linux-64 7.3.0 hdf63c60_1
        - gfortran_linux-64 7.3.0 h553295d_3
        - glib 2.56.2 had28632_1001
        - graphite2 1.3.12 hf484d3e_1001
        - gxx_impl_linux-64 7.3.0 hdf63c60_1
        - gxx_linux-64 7.3.0 h553295d_3
        - harfbuzz 1.9.0 he243708_1001
        - icu 58.2 hf484d3e_1000
        - jpeg 9c h14c3975_1001
        - krb5 1.16.2 hc83ff2d_1000
        - libcurl 7.63.0 h01ee5af_1000
        - libedit 3.1.20170329 hf8c457e_1001
        - libffi 3.2.1 hf484d3e_1005
        - libgcc-ng 7.3.0 hdf63c60_0
        - libgfortran-ng 7.3.0 hdf63c60_0
        - libiconv 1.15 h14c3975_1003
        - libpng 1.6.36 h84994c4_1000
        - libssh2 1.8.0 h1ad7b7a_1003
        - libstdcxx-ng 7.3.0 hdf63c60_0
        - libtiff 4.0.10 h648cc4a_1001
        - libuuid 2.32.1 h14c3975_1000
        - libxcb 1.13 h14c3975_1002
        - libxml2 2.9.8 h143f9aa_1005
        - make 4.2.1 h14c3975_2002
        - ncurses 6.1 hf484d3e_1002
        - openssl 1.0.2p h14c3975_1001
        - pango 1.40.14 h53a7087_1002
        - pcre 8.41 hf484d3e_1003
        - pixman 0.34.0 h14c3975_1003
        - pthread-stubs 0.4 h14c3975_1001
        - r-base 3.5.1 he45234b_1005
        - r-class 7.3_14 r351h96ca727_1002
        - r-e1071 1.7_0 r351h29659fb_1000
        - r-mass 7.3_50 r351h96ca727_1002
        - r-randomforest 4.6_14 r351ha65eedd_1000
        - readline 7.0 hf8c457e_1001
        - tk 8.6.9 h84994c4_1000
        - tktable 2.10 h14c3975_0
        - xorg-kbproto 1.0.7 h14c3975_1002
        - xorg-libice 1.0.9 h14c3975_1004
        - xorg-libsm 1.2.3 h4937e3b_1000
        - xorg-libx11 1.6.6 h14c3975_1000
        - xorg-libxau 1.0.8 h14c3975_1006
        - xorg-libxdmcp 1.1.2 h14c3975_1007
        - xorg-libxext 1.3.3 h14c3975_1004
        - xorg-libxrender 0.9.10 h14c3975_1002
        - xorg-renderproto 0.11.1 h14c3975_1002
        - xorg-xextproto 7.3.0 h14c3975_1002
        - xorg-xproto 7.0.31 h14c3975_1007
        - xz 5.2.4 h14c3975_1001
        - zlib 1.2.11 h14c3975_1003
    run:
        - bioconductor-biobase >=2.42.0,<2.43.0
        - bioconductor-ropls >=1.14.0,<1.15.0
        - r-base >=3.5.1,<3.5.2.0a0
        - r-e1071
        - r-randomforest
test:
    commands:
        - $R -e "library('biosigner')"
about:
    home: https://bioconductor.org/packages/3.8/bioc/html/biosigner.html
    license: CeCILL
    summary: Feature selection is critical in omics data analysis to extract restricted
        and meaningful molecular signatures from complex and high-dimension data,
        and to build robust classifiers. This package implements a new method to assess
        the relevance of the variables for the prediction performances of the classifier.
        The approach can be run in parallel with the PLS-DA, Random Forest, and SVM
        binary classifiers. The signatures and the corresponding 'restricted' models
        are returned, enabling future predictions on new datasets. A Galaxy implementation
        of the package is available within the Workflow4metabolomics.org online infrastructure
        for computational metabolomics.
extra:
    copy_test_source_files: true
    final: true
    identifiers:
        - biotools:biosigner
        - doi:10.3389/fmolb.2016.00026
