Add relion build script.
Builds from source based on git. Currently only gcc/7.4.0 is used. Better performance is reported with intel icc and MKL, but this would require additional openmpi variants. Variants for 3.0.8 and 3.1-beta (780dd7b) are installed.
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28
EM/relion/build
Executable file
28
EM/relion/build
Executable file
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#!/usr/bin/env modbuild
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pbuild::add_to_group 'EM'
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pbuild::use_cmake
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pbuild::prep() {
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local BRANCH
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if [[ "$V" =~ beta$ ]]; then
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BRANCH="ver${V_MAJOR}.${V_MINOR}"
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else
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BRANCH="${V_PKG}"
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fi
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git clone --depth=1 -b "$BRANCH" https://github.com/3dem/relion.git "$SRC_DIR" || return $?
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}
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pbuild::pre_configure() {
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pbuild::add_configure_args FORCE_OWN_FFTW=ON
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pbuild::add_configure_args FORCE_OWN_FLTK=ON
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pbuild::add_configure_args CUDA=ON
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pbuild::add_configure_args CudaTexture=ON
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pbuild::add_configure_args ALTCPU=ON
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pbuild::add_configure_args FORCE_OWN_TBB=ON
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# Requires intel compiler
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#pbuild::add_configure_args MKLFFT=ON
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}
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5
EM/relion/files/variants
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5
EM/relion/files/variants
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relion/2.1.b1 stable gcc/4.9.4 openmpi/2.0.1 cuda/8.0.44
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relion/3.0_beta stable gcc/4.9.4 openmpi/2.0.1 cuda/8.0.44
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relion/3.0.8 unstable gcc/7.4.0 openmpi/3.1.4_merlin6 cuda/9.2.148 b:cmake/3.14.0 b:tiff/4.0.9
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relion/3.1-beta unstable gcc/7.4.0 openmpi/3.1.4_merlin6 cuda/9.2.148 b:cmake/3.14.0 b:tiff/4.0.9
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27
EM/relion/modulefile
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27
EM/relion/modulefile
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#%Module1.0
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module-whatis "3D reconstructions or 2D class averages in electron cryo-microscopy (cryo-EM)"
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module-url "https://www2.mrc-lmb.cam.ac.uk/relion/index.php/Main_Page"
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module-license "GPLv2 license"
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module-maintainer "Spencer Bliven <spencer.bliven@psi.ch>"
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module-help "
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RELION (for REgularised LIkelihood OptimisatioN, pronounce rely-on) is a
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stand-alone computer program that employs an empirical Bayesian approach to
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refinement of (multiple) 3D reconstructions or 2D class averages in electron
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cryo-microscopy (cryo-EM). It is developed in the group of Sjors Scheres at the
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MRC Laboratory of Molecular Biology. Briefly, the ill-posed problem of
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3D-reconstruction is regularised by incorporating prior knowledge: the fact
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that macromolecular structures are smooth, i.e. they have limited power in the
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Fourier domain. In the corresponding Bayesian framework, many parameters of a
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statistical model are learned from the data, which leads to objective and
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high-quality results without the need for user expertise. The underlying theory
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is given in Scheres (2012) JMB. A more detailed description of its
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implementation is given in Scheres (2012) JSB. If RELION is useful in your
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work, please cite at least one of these papers.
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Scheres(2012) JMB http://www.sciencedirect.com/science/article/pii/S0022283611012290
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Scheres(2012) JSB http://www.sciencedirect.com/science/article/pii/S1047847712002481
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"
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