Commit 186d4b65 authored by bliven_s's avatar bliven_s
Browse files

Merge branch 'relion' into 'master'

Add relion build script.

See merge request Pmodules/buildblocks!64
parents 45310b1c 8190b0a6
# Relion
## Installation
Relion is installed from git. The ./build script should work for both stable
(tags) and unstable (branches) versions.
Currently only gcc/7.4.0 is used. Better performance is reported with
intel icc and MKL, but this would require additional openmpi variants.
#!/usr/bin/env modbuild
pbuild::add_to_group 'EM'
pbuild::prep() {
local BRANCH
if [[ "$V" =~ beta$ ]]; then
git clone --depth=1 -b "$BRANCH" "$SRC_DIR" || return $?
pbuild::pre_configure() {
pbuild::add_configure_args FORCE_OWN_FFTW=ON
pbuild::add_configure_args FORCE_OWN_FLTK=ON
pbuild::add_configure_args CUDA=ON
pbuild::add_configure_args CudaTexture=ON
pbuild::add_configure_args ALTCPU=ON
pbuild::add_configure_args FORCE_OWN_TBB=ON
# Requires intel compiler
#pbuild::add_configure_args MKLFFT=ON
relion/2.1.b1 stable gcc/4.9.4 openmpi/2.0.1 cuda/8.0.44
relion/3.0_beta stable gcc/4.9.4 openmpi/2.0.1 cuda/8.0.44
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
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
module-whatis "3D reconstructions or 2D class averages in electron cryo-microscopy (cryo-EM)"
module-url ""
module-license "GPLv2 license"
module-maintainer "Spencer Bliven <>"
module-help "
RELION (for REgularised LIkelihood OptimisatioN, pronounce rely-on) is a
stand-alone computer program that employs an empirical Bayesian approach to
refinement of (multiple) 3D reconstructions or 2D class averages in electron
cryo-microscopy (cryo-EM). It is developed in the group of Sjors Scheres at the
MRC Laboratory of Molecular Biology. Briefly, the ill-posed problem of
3D-reconstruction is regularised by incorporating prior knowledge: the fact
that macromolecular structures are smooth, i.e. they have limited power in the
Fourier domain. In the corresponding Bayesian framework, many parameters of a
statistical model are learned from the data, which leads to objective and
high-quality results without the need for user expertise. The underlying theory
is given in Scheres (2012) JMB. A more detailed description of its
implementation is given in Scheres (2012) JSB. If RELION is useful in your
work, please cite at least one of these papers.
Scheres(2012) JMB
Scheres(2012) JSB
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