# This file created by conda-build 3.21.8
# meta.yaml template originally from:
# /opt/recipe, last modified Tue Nov  8 09:20:48 2022
# ------------------------------------------------

package:
  name: bioconductor-lrcell
  version: 1.6.0
source:
  md5: b698cae5f254406d6f498bbcd32e08fa
  url:
    - https://bioarchive.galaxyproject.org/LRcell_1.6.0.tar.gz
    - https://bioconductor.org/packages/3.16/bioc/src/contrib/LRcell_1.6.0.tar.gz
    - https://depot.galaxyproject.org/software/bioconductor-lrcell/bioconductor-lrcell_1.6.0_src_all.tar.gz
build:
  noarch: generic
  number: '0'
  rpaths:
    - lib/
    - lib/R/lib/
  string: r42hdfd78af_0
requirements:
  host:
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    - libcblas 3.9.0 16_linux64_openblas
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    - libgcc-ng 12.2.0 h65d4601_19
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    - python 3.10.6 ha86cf86_0_cpython
    - python_abi 3.10 2_cp310
    - pyyaml 6.0 py310h5764c6d_5
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    - r-dbi 1.1.3 r42hc72bb7e_1
    - r-dbplyr 2.2.1 r42hc72bb7e_1
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    - r-diffobj 0.3.5 r42h06615bd_1
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    - r-dt 0.26 r42hc72bb7e_0
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    - r-fontawesome 0.4.0 r42hc72bb7e_0
    - r-formatr 1.12 r42hc72bb7e_1
    - r-fs 1.5.2 r42h7525677_2
    - r-futile.logger 1.4.3 r42hc72bb7e_1004
    - r-futile.options 1.0.1 r42hc72bb7e_1003
    - r-generics 0.1.3 r42hc72bb7e_1
    - r-ggplot2 3.4.0 r42hc72bb7e_0
    - r-ggrepel 0.9.2 r42h7525677_0
    - r-glue 1.6.2 r42h06615bd_1
    - r-gtable 0.3.1 r42hc72bb7e_1
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    - r-htmlwidgets 1.5.4 r42hc72bb7e_1
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    - r-lattice 0.20_45 r42h06615bd_1
    - r-lazyeval 0.2.2 r42h06615bd_3
    - r-lifecycle 1.0.3 r42hc72bb7e_1
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    - r-mass 7.3_58.1 r42h06615bd_1
    - r-matrix 1.5_1 r42h5f7b363_0
    - r-memoise 2.0.1 r42hc72bb7e_1
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    - r-plogr 0.2.0 r42hc72bb7e_1004
    - r-png 0.1_7 r42h06615bd_1006
    - r-praise 1.0.0 r42hc72bb7e_1006
    - r-processx 3.8.0 r42h06615bd_0
    - r-promises 1.2.0.1 r42h7525677_1
    - r-ps 1.7.2 r42h06615bd_0
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    - r-testthat 3.1.5 r42h7525677_1
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    - r-tidyselect 1.2.0 r42hc72bb7e_0
    - r-utf8 1.2.2 r42h06615bd_1
    - r-vctrs 0.5.0 r42h7525677_0
    - r-viridislite 0.4.1 r42hc72bb7e_1
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    - r-yaml 2.3.6 r42h06615bd_0
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    - sed 4.8 he412f7d_0
    - setuptools 65.5.1 pyhd8ed1ab_0
    - sysroot_linux-64 2.12 he073ed8_15
    - tk 8.6.12 h27826a3_0
    - tktable 2.10 hb7b940f_3
    - toml 0.10.2 pyhd8ed1ab_0
    - tzdata 2022f h191b570_0
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    - xmltodict 0.13.0 pyhd8ed1ab_0
    - xorg-kbproto 1.0.7 h7f98852_1002
    - xorg-libice 1.0.10 h7f98852_0
    - xorg-libsm 1.2.3 hd9c2040_1000
    - xorg-libx11 1.7.2 h7f98852_0
    - xorg-libxau 1.0.9 h7f98852_0
    - xorg-libxdmcp 1.1.3 h7f98852_0
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    - xorg-libxt 1.2.1 h7f98852_2
    - xorg-renderproto 0.11.1 h7f98852_1002
    - xorg-xextproto 7.3.0 h7f98852_1002
    - xorg-xproto 7.0.31 h7f98852_1007
    - xz 5.2.6 h166bdaf_0
    - yaml 0.2.5 h7f98852_2
    - yq 2.13.0 pyhd8ed1ab_0
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    - zstd 1.5.2 h6239696_4
  run:
    - bioconductor-annotationhub >=3.6.0,<3.7.0
    - bioconductor-biocparallel >=1.32.0,<1.33.0
    - bioconductor-experimenthub >=2.6.0,<2.7.0
    - r-base >=4.2,<4.3.0a0
    - r-dplyr
    - r-ggplot2
    - r-ggrepel
    - r-magrittr
test:
  commands:
    - $R -e "library('LRcell')"
about:
  description: 'The goal of LRcell is to identify specific sub-cell types that drives
    the changes observed in a bulk RNA-seq differential gene expression experiment.
    To achieve this, LRcell utilizes sets of cell marker genes acquired from single-cell
    RNA-sequencing (scRNA-seq) as indicators for various cell types in the tissue
    of interest. Next, for each cell type, using its marker genes as indicators, we
    apply Logistic Regression on the complete set of genes with differential expression
    p-values to calculate a cell-type significance p-value. Finally, these p-values
    are compared to predict which one(s) are likely to be responsible for the differential
    gene expression pattern observed in the bulk RNA-seq experiments. LRcell is inspired
    by the LRpath[@sartor2009lrpath] algorithm developed by Sartor et al., originally
    designed for pathway/gene set enrichment analysis. LRcell contains three major
    components: LRcell analysis, plot generation and marker gene selection. All modules
    in this package are written in R. This package also provides marker genes in the
    Prefrontal Cortex (pFC) human brain region, human PBMC and nine mouse brain regions
    (Frontal Cortex, Cerebellum, Globus Pallidus, Hippocampus, Entopeduncular, Posterior
    Cortex, Striatum, Substantia Nigra and Thalamus).'
  home: https://bioconductor.org/packages/3.16/bioc/html/LRcell.html
  license: MIT + file LICENSE
  license_file: LICENSE
  summary: Differential cell type change analysis using Logistic/linear Regression
extra:
  copy_test_source_files: true
  final: true
