# This file created by conda-build 3.21.8
# meta.yaml template originally from:
# /Users/runner/work/bioconda-recipes/bioconda-recipes/recipes/bioconductor-pcatools, last modified Fri Sep 16 06:44:50 2022
# ------------------------------------------------

package:
  name: bioconductor-pcatools
  version: 2.6.0
source:
  md5: 8707552e1bbf1b6b001141d53e9ea568
  url:
    - https://bioarchive.galaxyproject.org/PCAtools_2.6.0.tar.gz
    - https://bioconductor.org/packages/3.14/bioc/src/contrib/PCAtools_2.6.0.tar.gz
    - https://depot.galaxyproject.org/software/bioconductor-pcatools/bioconductor-pcatools_2.6.0_src_all.tar.gz
build:
  number: '2'
  rpaths:
    - lib/
    - lib/R/lib/
  string: r41hb890f52_2
requirements:
  build:
    - ca-certificates 2022.9.14 h033912b_0
    - cctools_osx-64 973.0.1 h3eff9a4_10
    - clang 14.0.4 h694c41f_0
    - clang-14 14.0.4 default_h55ffa42_0
    - clang_osx-64 14.0.4 h3a95cd4_2
    - clangxx 14.0.4 default_h55ffa42_0
    - clangxx_osx-64 14.0.4 he1dbc44_2
    - compiler-rt 14.0.4 h7fcd477_0
    - compiler-rt_osx-64 14.0.4 h6df654d_0
    - ld64_osx-64 609 h1e06c2b_10
    - libclang-cpp14 14.0.4 default_h55ffa42_0
    - libcxx 14.0.6 hccf4f1f_0
    - libllvm13 13.0.1 h64f94b2_2
    - libllvm14 14.0.4 h41df66c_0
    - libzlib 1.2.12 hfd90126_3
    - llvm-tools 14.0.4 h41df66c_0
    - make 4.3 h22f3db7_1
    - openssl 3.0.5 hfd90126_2
    - sigtool 0.1.3 h88f4db0_0
    - tapi 1100.0.11 h9ce4665_0
  host:
    - _r-mutex 1.0.1 anacondar_1
    - bioconductor-beachmat 2.10.0 r41hb890f52_2
    - bioconductor-biocgenerics 0.40.0 r41hdfd78af_0
    - bioconductor-biocparallel 1.28.3 r41hb890f52_1
    - bioconductor-biocsingular 1.10.0 r41hb890f52_2
    - bioconductor-delayedarray 0.20.0 r41h3be46a4_2
    - bioconductor-delayedmatrixstats 1.16.0 r41hdfd78af_0
    - bioconductor-iranges 2.28.0 r41h3be46a4_2
    - bioconductor-matrixgenerics 1.6.0 r41hdfd78af_0
    - bioconductor-s4vectors 0.32.4 r41h3be46a4_0
    - bioconductor-scaledmatrix 1.2.0 r41hdfd78af_0
    - bioconductor-sparsematrixstats 1.6.0 r41hb890f52_2
    - bwidget 1.9.14 h694c41f_1
    - bzip2 1.0.8 h0d85af4_4
    - c-ares 1.18.1 h0d85af4_0
    - ca-certificates 2022.9.14 h033912b_0
    - cairo 1.16.0 h904041c_1013
    - cctools_osx-64 973.0.1 h3eff9a4_10
    - clang 14.0.4 h694c41f_0
    - clang-14 14.0.4 default_h55ffa42_0
    - clang_osx-64 14.0.4 h3a95cd4_2
    - clangxx 14.0.4 default_h55ffa42_0
    - clangxx_osx-64 14.0.4 he1dbc44_2
    - compiler-rt 14.0.4 h7fcd477_0
    - compiler-rt_osx-64 14.0.4 h6df654d_0
    - curl 7.83.1 h23f1065_0
    - expat 2.4.8 h96cf925_0
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    - font-ttf-inconsolata 3.000 h77eed37_0
    - font-ttf-source-code-pro 2.038 h77eed37_0
    - font-ttf-ubuntu 0.83 hab24e00_0
    - fontconfig 2.14.0 h5bb23bf_1
    - fonts-conda-ecosystem 1 0
    - fonts-conda-forge 1 0
    - freetype 2.12.1 h3f81eb7_0
    - fribidi 1.0.10 hbcb3906_0
    - gettext 0.19.8.1 hd1a6beb_1008
    - gfortran_impl_osx-64 9.5.0 h2221f41_25
    - gfortran_osx-64 9.5.0 h18f7dce_0
    - gmp 6.2.1 h2e338ed_0
    - graphite2 1.3.13 h2e338ed_1001
    - gsl 2.7 h93259b0_0
    - harfbuzz 5.1.0 h00bb2c2_0
    - icu 70.1 h96cf925_0
    - isl 0.22.1 hb1e8313_2
    - jpeg 9e hac89ed1_2
    - krb5 1.19.3 hb98e516_0
    - ld64_osx-64 609 h1e06c2b_10
    - lerc 4.0.0 hb486fe8_0
    - libblas 3.9.0 5_h0661a58_netlib
    - libcblas 3.9.0 5_h0661a58_netlib
    - libclang-cpp14 14.0.4 default_h55ffa42_0
    - libcurl 7.83.1 h23f1065_0
    - libcxx 14.0.6 hccf4f1f_0
    - libdeflate 1.14 hb7f2c08_0
    - libedit 3.1.20191231 h0678c8f_2
    - libev 4.33 haf1e3a3_1
    - libffi 3.4.2 h0d85af4_5
    - libgfortran 5.0.0 10_4_0_h97931a8_25
    - libgfortran-devel_osx-64 9.5.0 hc2d6858_25
    - libgfortran5 11.3.0 h082f757_25
    - libglib 2.72.1 hfbcb929_0
    - libiconv 1.16 haf1e3a3_0
    - liblapack 3.9.0 5_h0661a58_netlib
    - libllvm13 13.0.1 h64f94b2_2
    - libllvm14 14.0.4 h41df66c_0
    - libnghttp2 1.47.0 h5aae05b_1
    - libpng 1.6.37 h5481273_4
    - libssh2 1.10.0 h47af595_3
    - libtiff 4.4.0 hdb44e8a_4
    - libwebp-base 1.2.4 h775f41a_0
    - libxml2 2.9.14 hea49891_4
    - libzlib 1.2.12 hfd90126_3
    - llvm-openmp 14.0.4 ha654fa7_0
    - llvm-tools 14.0.4 h41df66c_0
    - make 4.3 h22f3db7_1
    - mpc 1.2.1 hbb51d92_0
    - mpfr 4.1.0 h0f52abe_1
    - ncurses 6.3 h96cf925_1
    - openssl 3.0.5 hfd90126_2
    - pango 1.50.9 hc8ec20f_0
    - pcre 8.45 he49afe7_0
    - pcre2 10.37 h3f55489_1
    - pixman 0.40.0 hbcb3906_0
    - r-backports 1.4.1 r41h28b5c78_0
    - r-base 4.1.3 h85fa70c_2
    - r-bh 1.78.0_0 r41hc72bb7e_0
    - r-brio 1.1.3 r41h28b5c78_0
    - r-callr 3.7.2 r41hc72bb7e_0
    - r-cli 3.4.0 r41h49197e3_0
    - r-colorspace 2.0_3 r41h0f1d5c4_0
    - r-cowplot 1.1.1 r41hc72bb7e_0
    - r-crayon 1.5.1 r41hc72bb7e_0
    - r-desc 1.4.2 r41hc72bb7e_0
    - r-diffobj 0.3.5 r41h28b5c78_0
    - r-digest 0.6.29 r41h9951f98_0
    - r-dqrng 0.3.0 r41h8619c4b_0
    - r-ellipsis 0.3.2 r41h28b5c78_0
    - r-evaluate 0.16 r41hc72bb7e_0
    - r-fansi 1.0.3 r41h0f1d5c4_0
    - r-farver 2.1.1 r41h8619c4b_0
    - r-formatr 1.12 r41hc72bb7e_0
    - r-fs 1.5.2 r41hc4bb905_1
    - r-futile.logger 1.4.3 r41hc72bb7e_1003
    - r-futile.options 1.0.1 r41hc72bb7e_1002
    - r-ggplot2 3.3.6 r41hc72bb7e_0
    - r-ggrepel 0.9.1 r41h9951f98_0
    - r-glue 1.6.2 r41h0f1d5c4_0
    - r-gtable 0.3.1 r41hc72bb7e_0
    - r-irlba 2.3.5 r41ha69ffb1_0
    - r-isoband 0.2.5 r41h9951f98_0
    - r-jsonlite 1.8.0 r41h0f1d5c4_0
    - r-labeling 0.4.2 r41hc72bb7e_1
    - r-lambda.r 1.2.4 r41hc72bb7e_1
    - r-lattice 0.20_45 r41h28b5c78_0
    - r-lifecycle 1.0.2 r41hc72bb7e_0
    - r-magrittr 2.0.3 r41h0f1d5c4_0
    - r-mass 7.3_58.1 r41hef1f586_0
    - r-matrix 1.4_1 r41ha2825d1_0
    - r-matrixstats 0.62.0 r41h0f1d5c4_0
    - r-mgcv 1.8_40 r41h60b693f_0
    - r-munsell 0.5.0 r41hc72bb7e_1004
    - r-nlme 3.1_159 r41h225c1e1_0
    - r-pillar 1.8.1 r41hc72bb7e_0
    - r-pkgconfig 2.0.3 r41hc72bb7e_1
    - r-pkgload 1.3.0 r41hc72bb7e_0
    - r-plyr 1.8.7 r41hc4bb905_0
    - r-praise 1.0.0 r41hc72bb7e_1005
    - r-processx 3.7.0 r41h67d6963_0
    - r-ps 1.7.1 r41h67d6963_0
    - r-r6 2.5.1 r41hc72bb7e_0
    - r-rcolorbrewer 1.1_3 r41h785f33e_0
    - r-rcpp 1.0.9 r41h49197e3_1
    - r-rematch2 2.1.2 r41hc72bb7e_1
    - r-reshape2 1.4.4 r41h9951f98_1
    - r-rlang 1.0.5 r41h49197e3_0
    - r-rprojroot 2.0.3 r41hc72bb7e_0
    - r-rsvd 1.0.5 r41hc72bb7e_0
    - r-scales 1.2.1 r41hc72bb7e_0
    - r-sitmo 2.0.2 r41h8619c4b_0
    - r-snow 0.4_4 r41hc72bb7e_0
    - r-stringi 1.7.8 r41hcb6f7a5_0
    - r-stringr 1.4.1 r41hc72bb7e_0
    - r-testthat 3.1.4 r41h8619c4b_0
    - r-tibble 3.1.8 r41h67d6963_0
    - r-utf8 1.2.2 r41h28b5c78_0
    - r-vctrs 0.4.1 r41hc4bb905_0
    - r-viridislite 0.4.1 r41hc72bb7e_0
    - r-waldo 0.4.0 r41hc72bb7e_0
    - r-withr 2.5.0 r41hc72bb7e_0
    - readline 8.1.2 h3899abd_0
    - sigtool 0.1.3 h88f4db0_0
    - tapi 1100.0.11 h9ce4665_0
    - tk 8.6.12 h5dbffcc_0
    - tktable 2.10 h49f0cf7_3
    - xz 5.2.6 h775f41a_0
    - zlib 1.2.12 hfd90126_3
    - zstd 1.5.2 hfa58983_4
  run:
    - bioconductor-beachmat >=2.10.0,<2.11.0
    - bioconductor-biocparallel >=1.28.0,<1.29.0
    - bioconductor-biocsingular >=1.10.0,<1.11.0
    - bioconductor-delayedarray >=0.20.0,<0.21.0
    - bioconductor-delayedmatrixstats >=1.16.0,<1.17.0
    - libblas >=3.9.0,<4.0a0
    - libcxx >=14.0.4
    - liblapack >=3.9.0,<4.0a0
    - r-base >=4.1,<4.2.0a0
    - r-bh
    - r-cowplot
    - r-dqrng
    - r-ggplot2
    - r-ggrepel
    - r-lattice
    - r-matrix
    - r-rcpp
    - r-reshape2
test:
  commands:
    - $R -e "library('PCAtools')"
about:
  description: Principal Component Analysis (PCA) is a very powerful technique that
    has wide applicability in data science, bioinformatics, and further afield. It
    was initially developed to analyse large volumes of data in order to tease out
    the differences/relationships between the logical entities being analysed. It
    extracts the fundamental structure of the data without the need to build any model
    to represent it. This 'summary' of the data is arrived at through a process of
    reduction that can transform the large number of variables into a lesser number
    that are uncorrelated (i.e. the 'principal components'), while at the same time
    being capable of easy interpretation on the original data. PCAtools provides functions
    for data exploration via PCA, and allows the user to generate publication-ready
    figures. PCA is performed via BiocSingular - users can also identify optimal number
    of principal components via different metrics, such as elbow method and Horn's
    parallel analysis, which has relevance for data reduction in single-cell RNA-seq
    (scRNA-seq) and high dimensional mass cytometry data.
  home: https://bioconductor.org/packages/3.14/bioc/html/PCAtools.html
  license: GPL-3
  license_file: /Users/runner/miniconda/conda-bld/bioconductor-pcatools_1663319277836/_h_env_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehol/lib/R/share/licenses/GPL-3
  summary: 'PCAtools: Everything Principal Components Analysis'
extra:
  copy_test_source_files: true
  final: true
