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New package: r-biomartr (#14812)

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This PR creates the r-biomartr package as well as needed new packages
and updates.

- new dependency: r-philentropy
- update: r-curl
This commit is contained in:
Glenn Johnson 2020-02-10 04:08:04 -06:00 committed by GitHub
parent cb3dbea198
commit 745a843911
3 changed files with 77 additions and 3 deletions
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44
var/spack/repos/builtin/packages/r-biomartr/package.py Normal file
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# Copyright 2013-2020 Lawrence Livermore National Security, LLC and other
# Spack Project Developers. See the top-level COPYRIGHT file for details.
#
# SPDX-License-Identifier: (Apache-2.0 OR MIT)
from spack import *
class RBiomartr(RPackage):
"""Perform large scale genomic data retrieval and functional annotation
retrieval. This package aims to provide users with a standardized way to
automate genome, proteome, 'RNA', coding sequence ('CDS'), 'GFF', and
metagenome retrieval from 'NCBI RefSeq', 'NCBI Genbank', 'ENSEMBL',
'ENSEMBLGENOMES', and 'UniProt' databases. Furthermore, an interface to the
'BioMart' database (Smedley et al. (2009) <doi:10.1186/1471-2164-10-22>)
allows users to retrieve functional annotation for genomic loci. In
addition, users can download entire databases such as 'NCBI RefSeq' (Pruitt
et al. (2007) <doi:10.1093/nar/gkl842>), 'NCBI nr', 'NCBI nt', 'NCBI
Genbank' (Benson et al. (2013) <doi:10.1093/nar/gks1195>), etc. as well as
'ENSEMBL' and 'ENSEMBLGENOMES' with only one command."""
homepage = "https://docs.ropensci.org/biomartr"
url = "https://cloud.r-project.org/src/contrib/biomartr_0.9.2.tar.gz"
list_url = "https://cloud.r-project.org/src/contrib/Archive/biomartr"
version('0.9.2', sha256='d88085696e9c5614828602254c33f2cdd3bbfeebc2f21a705eee3cb961097c89')
depends_on('r-biomart', type=('build', 'run'))
depends_on('r-biostrings', type=('build', 'run'))
depends_on('r-curl', type=('build', 'run'))
depends_on('r-tibble', type=('build', 'run'))
depends_on('r-jsonlite', type=('build', 'run'))
depends_on('r-data-table@1.9.4:', type=('build', 'run'))
depends_on('r-dplyr@0.3.0:', type=('build', 'run'))
depends_on('r-readr@0.2.2:', type=('build', 'run'))
depends_on('r-downloader@0.3:', type=('build', 'run'))
depends_on('r-rcurl@1.95-4.5:', type=('build', 'run'))
depends_on('r-xml@3.98-1.1:', type=('build', 'run'))
depends_on('r-httr@0.6.1:', type=('build', 'run'))
depends_on('r-stringr@0.6.2:', type=('build', 'run'))
depends_on('r-purrr', type=('build', 'run'))
depends_on('r-r-utils', type=('build', 'run'))
depends_on('r-philentropy', type=('build', 'run'))
depends_on('r-fs@1.3.1:', type=('build', 'run'))

8
var/spack/repos/builtin/packages/r-curl/package.py
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@ -21,12 +21,14 @@ class RCurl(RPackage):
url = "https://cloud.r-project.org/src/contrib/curl_2.3.tar.gz"
list_url = "https://cloud.r-project.org/src/contrib/Archive/curl"
version('4.3', sha256='7406d485bb50a6190e3ed201e3489063fd249b8b3b1b4f049167ac405a352edb')
version('4.0', sha256='09a99c9c86666449188fbb211cb1e9fbdb5108ab56f0d09322cd0ae50e926171')
version('3.3', sha256='0cb0b9a9280edc42ebed94708541ec86b4f48779e722171e45227eab8a88a5bd')
version('3.0', sha256='7bf8e3ae7cc77802ae300277e85d925d4c0611a9b7dad5c5601e0d2cbe14a506')
version('2.3', sha256='f901dad6bb70a6875a85da75bcbb42afffdcdf4ef221909733826bcb012d7c3d')
version('1.0', sha256='f8927228754fdfb21dbf08b9e67c5f97e06764c4adf327a4126eed84b1508f3d')
version('2.3', sha256='f901dad6bb70a6875a85da75bcbb42afffdcdf4ef221909733826bcb012d7c3d')
version('1.0', sha256='f8927228754fdfb21dbf08b9e67c5f97e06764c4adf327a4126eed84b1508f3d')
version('0.9.7', sha256='46e150998723fd1937da598f47f49fe47e40c1f57ec594436c6ef1e0145b44dc')
depends_on('r@3.0.0:', type=('build', 'run'))
depends_on('curl')
depends_on('curl', when='@4.3:')
depends_on('curl@:7.63', when='@:4.0')

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# Copyright 2013-2020 Lawrence Livermore National Security, LLC and other
# Spack Project Developers. See the top-level COPYRIGHT file for details.
#
# SPDX-License-Identifier: (Apache-2.0 OR MIT)
from spack import *
class RPhilentropy(RPackage):
"""Computes 46 optimized distance and similarity measures for comparing
probability functions (Drost (2018) <doi:10.21105/joss.00765>). These
comparisons between probability functions have their foundations in a broad
range of scientific disciplines from mathematics to ecology. The aim of
this package is to provide a core framework for clustering, classification,
statistical inference, goodness-of-fit, non-parametric statistics,
information theory, and machine learning tasks that are based on comparing
univariate or multivariate probability functions."""
homepage = "https://github.com/HajkD/philentropy"
url = "https://cloud.r-project.org/src/contrib/philentropy_0.4.0.tar.gz"
list_url = "https://cloud.r-project.org/src/contrib/Archive/philentropy"
version('0.4.0', sha256='bfd30bf5635aab6a82716299a87d44cf96c7ab7f4ee069843869bcc85c357127')
depends_on('r@3.1.2:', type=('build', 'run'))
depends_on('r-rcpp', type=('build', 'run'))
depends_on('r-dplyr', type=('build', 'run'))
depends_on('r-kernsmooth', type=('build', 'run'))