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academic/hyphy: Added (Hypothesis Testing using Phylogenies).
Signed-off-by: David Spencer <idlemoor@slackbuilds.org>
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53
academic/hyphy/README
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academic/hyphy/README
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HyPhy: Hypothesis testing using Phylogenies
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HyPhy is an open-source software package for the analysis of genetic
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sequences (in particular the inference of natural selection) using
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techniques in phylogenetics, molecular evolution, and machine learning.
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It features a rich scripting language for limitless customization of
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analyses. Additionally, HyPhy features support for parallel computing
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environments (via message passing interface).
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HyPhy was designed to allow the specification and fitting of a broad
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class of continuous-time discrete-space Markov models of sequence
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evolution. To implement these models, HyPhy provides its own scripting
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language - HBL, or HyPhy Batch Language, which can be used to develop
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custom analyses or modify existing ones. Importantly, it is not
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necessary to learn (or even be aware of) HBL in order to use HyPhy, as
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most common models and analyses have been implemented for user
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convenience. Once a model is defined, it can be fitted to data (using a
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fixed topology tree), its parameters can be constrained in user-defined
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ways to test various hypotheses (e.g. is rate1 > rate2), and simulate
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data from. HyPhy primarily implements maximum likelihood methods, but
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it can also be used to perform some forms of Bayesian inference (e.g.
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FUBAR), fit Bayesian graphical models to data, run genetic algorithms to
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perform complex model selection.
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Features
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- Support for arbitrary sequence data, including nucleotide, amino-acid,
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codon, binary, count (microsattelite) data, including multiple
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partitions mixing differen data types.
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- Complex models of rate variation, including site-to-site, branch-to-
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branch, hidden markov model (autocorrelated rates), between/within
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partitions, and co-varion type models.
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- Fast numerical fitting routines, supporting parallel and distributed
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execution.
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- A broad collection of pre-defined evolutionary models.
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- The ability to specify flexible constraints on model parameters and
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estimate confidence intervals on MLEs.
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- Ancestral sequence reconstruction and sampling.
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- Simulate data from any model that can be defined and fitted in the
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language.
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- Apply unique (for this domain) machine learning methods to discover
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patterns in the data, e.g. genetic algorithms, stochastic context free
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grammars, Bayesian graphical models.
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- Script analyses completely in HBL including flow control, I/O,
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parallelization, etc.
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Registration
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you are highly advised to fill the registration form found at:
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https://veg.github.io/hyphy-site/register/
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Citing
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Sergei L. Kosakovsky Pond, Simon D. W. Frost and Spencer V. Muse (2005)
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HyPhy: hypothesis testing using phylogenies.
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Bioinformatics 21(5): 676-679
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academic/hyphy/References
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academic/hyphy/References
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HyPhy
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Sergei L. Kosakovsky Pond, Simon D. W. Frost and Spencer V. Muse (2005)
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HyPhy: hypothesis testing using phylogenies. Bioinformatics 21(5): 676-679
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Datamonkey webserver
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Wayne Delport, Art F. Poon, Simon D. W. Frost and Sergei L. Kosakovsky Pond.
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Datamonkey 2010: a suite of phylogenetic analysis tools for evolutionary biology. Bioinformatics 2010 July 29[Epub ahead of print; PMID: 20671151]
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Sergei L. Kosakovsky Pond and Simon D. W. Frost (2005). Datamonkey: rapid detection of selective pressure on individual sites of codon alignments. Bioinformatics 21(10): 2531-2533
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Specific methods implemented in HyPhy
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Selection detection (SLAC/FEL/REL) - Sergei L. Kosakovsky Pond and Simon D. W. Frost (2005) Not So Different After All: A Comparison of Methods for Detecting Amino Acid Sites Under Selection. Molecular Biology and Evolution 22(5): 1208-1222
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Internal Fixed Effects Likelihood (IFEL) Sergei L Kosakovsky Pond, Simon DW Frost, Zehava Grossman, Michael B Gravenor, Douglas D Richman and Andrew J Leigh Brown (2006). Adaptation to different human populations by HIV-1 revealed by codon-based analyses. PLoS Computational Biology 2(6): e62
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TOGGLE - Wayne Delport, Konrad Scheffler and Cathal Seoighe (2008). Frequent Toggling between Alternative Amino Acids Is Driven by Selection in HIV-1. PLoS Pathogens 4(12): e1000242.
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Directional Evolution in Protein Sequences (DEPS) Sergei L Kosakovsky Pond, Art FY Poon, Andrew J Leigh Brown and Simon Frost (2008). A Maximum Likelihood Method for Detecting Directional Evolution in Protein Sequences and Its Application to Influenza A Virus. Molecular Biology and Evolution 25(9): 1809-1824
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PARRIS - Konrad Scheffler,Darren P. Martin and Cathal Seoighe (2006). Robust inference of positive selection from recombining coding sequences. Bioinformatics 22(20): 2493-2499
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GA-Branch - S.L. Kosakovsky Pond and S.D.W. Frost (2005). A Genetic Algorithm Approach to Detecting Lineage-specific Variation in Selection Pressure. Molecular Biology and Evolution 22(3): 478-485
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Evolutionary Selection Distance (ESD) Sergei L Kosakovsky Pond, Konrad Scheffler, Michael B Gravenor, Art FY Poon and Simon DW Frost (2009).
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Evolutionary Fingerprinting of Genes. Molecular Biology and Evolution 27(3): 520-536
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Spidermonkey/BGM - Art Poon, Fraser Lewis, Sergei Kosakovsky Pond and Simon Frost (2007). An evolutionary-network model reveals stratified interactions in the V3 loop of the HIV-1 envelope. PLoS Computational Biology 3(11): e23
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Codon Model Selection (CMS) - Wayne Delport, Konrad Scheffler, Gordon Botha, Michael B Gravenor, Spencer V. Muse and Sergei L Kosakovsky Pond (2010) CodonTest: modeling amino-acid substitution preferences in coding sequences. PLoS Computational Biology 6(8): e1000885
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Branch-site REL - Sergei L. Kosakovsky Pond1, Ben Murrell, Mathieu Fourment, Simon D. W. Frost, Wayne Delport and Konrad Scheffler (2011)
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A random effects branch-site model for detecting episodic diversifying selection. Molecular Biology and Evolution (first published online June 13, 2011 doi:10.1093/ molbev/msr125)
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MEME - Murrell, B., Wertheim, J. O., Moola, S., Weighill, T., Scheffler, K., and Kosakovsky Pond, S. L. (2012) Detecting Individual Sites Subject to Episodic Diversifying Selection". PLoS Genet, 8(7), e1002764+
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SBP/GARD - Sergei L Kosakovsky Pond, David Posada, Michael B Gravenor, Christopher H Woelk and Simon DW Frost. Automated Phylogenetic Detection of Recombination Using a Genetic Algorithm. Molecular Biology and Evolution 23(10): 1891-1901
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SCUEAL - Sergei L Kosakovsky Pond, David Posada, Eric Stawiski, Colombe Chappey, Art FY Poon, Gareth Hughes, Esther Fearnhill, Mike B Gravenor, Andrew J Leigh Brown and Simon DW Frost (2009). An Evolutionary Model-Based Algorithm for Accurate Phylogenetic Breakpoint Mapping and Subtype Prediction in HIV-1. PLoS Computational Biology 5(11): e1000581
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Ancestral Sequence Reconstruction (ASR) (joint) - Tal Pupko, Itsik Pe'er Ron Shamir and Dan Graur (2000). A Fast Algorithm for Joint Reconstruction of Ancestral Amino Acid Sequences. Molecular Biology and Evolution 17: 890-896
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ASR (marginal) - Z Yang, S Kumar and M Nei (1995). A New Method of Inference of Ancestral Nucleotide and Amino Acid Sequences. Genetics 141: 1641-1650
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ASR (sampled) - Rasmus Nielsen (2002) Mapping mutations on phylogenies. Systematic Biology 51(5): 729-739
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academic/hyphy/hyphy.SlackBuild
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academic/hyphy/hyphy.SlackBuild
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#!/bin/sh
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# Slackware build script for hyphy
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# Copyright 2017 Petar Petrov slackalaxy@gmail.com
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# All rights reserved.
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#
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# Redistribution and use of this script, with or without modification, is
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# permitted provided that the following conditions are met:
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#
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# 1. Redistributions of this script must retain the above copyright
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# notice, this list of conditions and the following disclaimer.
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#
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# THIS SOFTWARE IS PROVIDED BY THE AUTHOR "AS IS" AND ANY EXPRESS OR IMPLIED
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# WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
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# MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO
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# EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
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# SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
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# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
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# OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
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# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
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# OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF
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# ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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PRGNAM=hyphy
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VERSION=${VERSION:-2.3.4}
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BUILD=${BUILD:-1}
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TAG=${TAG:-_SBo}
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if [ -z "$ARCH" ]; then
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case "$( uname -m )" in
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i?86) ARCH=i586 ;;
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arm*) ARCH=arm ;;
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*) ARCH=$( uname -m ) ;;
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esac
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fi
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CWD=$(pwd)
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TMP=${TMP:-/tmp/SBo}
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PKG=$TMP/package-$PRGNAM
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OUTPUT=${OUTPUT:-/tmp}
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if [ "$ARCH" = "i586" ]; then
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SLKCFLAGS="-O2 -march=i586 -mtune=i686"
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LIBDIRSUFFIX=""
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elif [ "$ARCH" = "i686" ]; then
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SLKCFLAGS="-O2 -march=i686 -mtune=i686"
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LIBDIRSUFFIX=""
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elif [ "$ARCH" = "x86_64" ]; then
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SLKCFLAGS="-O2 -fPIC"
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LIBDIRSUFFIX="64"
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else
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SLKCFLAGS="-O2"
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LIBDIRSUFFIX=""
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fi
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set -e
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rm -rf $PKG
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mkdir -p $TMP $PKG $OUTPUT
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cd $TMP
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rm -rf $PRGNAM-$VERSION
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tar xvf $CWD/$PRGNAM-$VERSION.tar.gz
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cd $PRGNAM-$VERSION
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chown -R root:root .
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find -L . \
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\( -perm 777 -o -perm 775 -o -perm 750 -o -perm 711 -o -perm 555 \
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-o -perm 511 \) -exec chmod 755 {} \; -o \
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\( -perm 666 -o -perm 664 -o -perm 640 -o -perm 600 -o -perm 444 \
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-o -perm 440 -o -perm 400 \) -exec chmod 644 {} \;
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# Fix the libraries path on 64 systems
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sed -i "s:lib/hyphy:lib${LIBDIRSUFFIX}/hyphy:g" CMakeLists.txt
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mkdir -p build
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cd build
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cmake \
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-DCMAKE_C_FLAGS:STRING="$SLKCFLAGS" \
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-DCMAKE_CXX_FLAGS:STRING="$SLKCFLAGS" \
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-DCMAKE_REQUIRED_FLAGS="$SLKCFLAGS" \
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-DDEFAULT_COMPILE_FLAGS="$SLKCFLAGS" \
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-DINSTALL_PREFIX=/usr \
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-DCMAKE_BUILD_TYPE=Release ..
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# This builds build a HyPhy executable (HYPHYMP) using pthreads to do multiprocessing
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make MP
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make install DESTDIR=$PKG
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cd ..
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find $PKG -print0 | xargs -0 file | grep -e "executable" -e "shared object" | grep ELF \
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| cut -f 1 -d : | xargs strip --strip-unneeded 2> /dev/null || true
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# Include a few examples
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mkdir -p $PKG/usr/share/$PRGNAM
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cp -a Examples $PKG/usr/share/$PRGNAM
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mkdir -p $PKG/usr/doc/$PRGNAM-$VERSION
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cp -a help/*.pdf LICENSE README.md $PKG/usr/doc/$PRGNAM-$VERSION
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cat $CWD/$PRGNAM.SlackBuild > $PKG/usr/doc/$PRGNAM-$VERSION/$PRGNAM.SlackBuild
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cat $CWD/References > $PKG/usr/doc/$PRGNAM-$VERSION/References
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mkdir -p $PKG/install
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cat $CWD/slack-desc > $PKG/install/slack-desc
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cd $PKG
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/sbin/makepkg -l y -c n $OUTPUT/$PRGNAM-$VERSION-$ARCH-$BUILD$TAG.${PKGTYPE:-tgz}
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academic/hyphy/hyphy.info
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academic/hyphy/hyphy.info
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PRGNAM="hyphy"
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VERSION="2.3.4"
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HOMEPAGE="https://veg.github.io/hyphy-site/"
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DOWNLOAD="https://github.com/veg/hyphy/archive/2.3.4/hyphy-2.3.4.tar.gz"
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MD5SUM="1377f4973f40c7d336cb8d7c81a0bd34"
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DOWNLOAD_x86_64=""
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MD5SUM_x86_64=""
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REQUIRES=""
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MAINTAINER="Petar Petrov"
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EMAIL="slackalaxy@gmail.com"
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academic/hyphy/slack-desc
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academic/hyphy/slack-desc
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# HOW TO EDIT THIS FILE:
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# The "handy ruler" below makes it easier to edit a package description.
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# Line up the first '|' above the ':' following the base package name, and
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# the '|' on the right side marks the last column you can put a character in.
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# You must make exactly 11 lines for the formatting to be correct. It's also
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# customary to leave one space after the ':' except on otherwise blank lines.
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|-----handy-ruler------------------------------------------------------|
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hyphy: hyphy (Hypothesis Testing using Phylogenies)
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hyphy:
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hyphy: HyPhy is a software package for the analysis of genetic sequences,
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hyphy: in particular the inference of natural selection, using techniques
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hyphy: in phylogenetics, molecular evolution, and machine learning. It
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hyphy: features a rich scripting language for limitless customization of
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hyphy: analyses.
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hyphy:
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hyphy: Home: https://veg.github.io/hyphy-site/
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hyphy:
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hyphy:
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