r-gdsfmt: new package (#7035)
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var/spack/repos/builtin/packages/r-gdsfmt/package.py
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var/spack/repos/builtin/packages/r-gdsfmt/package.py
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##############################################################################
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# Copyright (c) 2013-2017, Lawrence Livermore National Security, LLC.
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# Produced at the Lawrence Livermore National Laboratory.
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#
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# This file is part of Spack.
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# Created by Todd Gamblin, tgamblin@llnl.gov, All rights reserved.
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# LLNL-CODE-647188
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#
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# For details, see https://github.com/spack/spack
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# Please also see the NOTICE and LICENSE files for our notice and the LGPL.
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#
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# This program is free software; you can redistribute it and/or modify
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# it under the terms of the GNU Lesser General Public License (as
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# published by the Free Software Foundation) version 2.1, February 1999.
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#
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# This program is distributed in the hope that it will be useful, but
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# WITHOUT ANY WARRANTY; without even the IMPLIED WARRANTY OF
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the terms and
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# conditions of the GNU Lesser General Public License for more details.
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#
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# You should have received a copy of the GNU Lesser General Public
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# License along with this program; if not, write to the Free Software
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# Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
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##############################################################################
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from spack import *
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class RGdsfmt(RPackage):
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"""This package provides a high-level R interface to CoreArray Genomic
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Data Structure (GDS) data files, which are portable across platforms
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with hierarchical structure to store multiple scalable array-oriented
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data sets with metadata information. It is suited for large-scale
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datasets, especially for data which are much larger than the available
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random-access memory. The gdsfmt package offers the efficient
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operations specifically designed for integers of less than 8 bits,
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since a diploid genotype, like single-nucleotide polymorphism (SNP),
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usually occupies fewer bits than a byte. Data compression and
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decompression are available with relatively efficient random access.
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It is also allowed to read a GDS file in parallel with multiple R
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processes supported by the package parallel."""
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homepage = "http://bioconductor.org/packages/gdsfmt/"
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url = "https://git.bioconductor.org/packages/gdsfmt"
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version('1.14.1', git='https://git.bioconductor.org/packages/gdsfmt', commit='15743647b7eea5b82d3284858b4591fb6e59959d')
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depends_on('r@3.4.0:3.4.9', when='@1.14.1')
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