hyphy

HyPhy: Hypothesis testing using Phylogenies

https://github.com/veg/hyphy

Science Score: 36.0%

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    13 of 38 committers (34.2%) from academic institutions
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    Low similarity (17.4%) to scientific vocabulary

Keywords

bioinformatics c-plus-plus comparative-genomics evolution phylogenetics science statistical-methods

Keywords from Contributors

sequences genomics dna workflow-engine ngs usegalaxy argument-parser software
Last synced: 6 months ago · JSON representation

Repository

HyPhy: Hypothesis testing using Phylogenies

Basic Info
  • Host: GitHub
  • Owner: veg
  • License: other
  • Language: HyPhy
  • Default Branch: master
  • Homepage: http://www.hyphy.org
  • Size: 57.9 MB
Statistics
  • Stars: 239
  • Watchers: 21
  • Forks: 69
  • Open Issues: 11
  • Releases: 101
Topics
bioinformatics c-plus-plus comparative-genomics evolution phylogenetics science statistical-methods
Created over 14 years ago · Last pushed 6 months ago
Metadata Files
Readme Contributing License

README.md

Build Status

HyPhy - Hypothesis testing using Phylogenies

HyPhy is an open-source software package for the analysis of genetic sequences using techniques in phylogenetics, molecular evolution, and machine learning. It features a complete graphical user interface (GUI) and a rich scripting language for limitless customization of analyses. Additionally, HyPhy features support for parallel computing environments (via message passing interface (MPI)) and it can be compiled as a shared library and called from other programming environments such as Python and R. HyPhy is the computational backbone powering datamonkey.org. Additional information is available at hyphy.org.

Quick Start

Install

conda install -c bioconda hyphy

Running with Docker

You can also run HyPhy without having to install it on your system using the provided Dockerfile. Following the below instructions starts an interactive Docker container where HyPhy is already available.

If you don't have Docker installed, first look at Docker Desktop.

Please note you must change this code snippet to point to the appropriate location for your input data. This will be made available inside the container at /hyphy/data.

git clone https://github.com/veg/hyphy.git cd hyphy docker build -t hyphy:latest . docker run --rm -v [path-to-your-input-data]:/hyphy/data -it hyphy:latest

Run with Command Line Arguments

hyphy <method_name> --alignment <path_to_alignment_file> <additional_method_specific_arguments>
+ `<methodname>is the name of the analysis you wish to run (can be: absrel, bgm, busted, fade, fel, fubar, gard, meme, relax or slac)_ + _is the relative or absolute path to a fasta, nexus or phylib file containing an alignment and tree_ + _A list of the availablecan be seen by runninghyphy --help`_

or

Run in Interactive Mode

hyphy -i

Building from Source

Requirements

  • cmake >= 3.12
  • gcc >= 4.9
  • libcurl
  • libpthread
  • openmp (can be installed on mac via brew install libomp)

Download

You can download a specific release here or clone this repo with

git clone https://github.com/veg/hyphy.git

Change your directory to the downloaded/cloned directory

cd hyphy

Build

cmake .

make install

Additional Options for Building from Source

Build Systems

If you prefer to use other build systems, such as Xcode, configure using the -G switch

cmake -G Xcode .

CMake supports a number of build system generators, feel free to peruse these and use them if you wish.

If you are on an OS X platform, you can specify which OS X SDK to use

cmake -DCMAKE_OSX_SYSROOT=/Developer/SDKs/MacOSX10.9.sdk/ .

If building on a heterogeneous cluster with some nodes that do not support auto-vectorization

cmake -DNOAVX=ON ..

If you're on a UNIX-compatible system, and you're comfortable with GNU make, then run make with one of the following build targets:

  • MP or hyphy - build a HyPhy executable (This used to be "HYPHYMP" but is now just "hyphy") using pthreads to do multiprocessing
  • MPI or HYPHYMPI - build a HyPhy executable (HYPHYMPI) using openMPI to do multiprocessing
  • LIB - build a HyPhy library (libhyphy_mp) using pthreads to do multiprocessing
  • GTEST - build HyPhy's gtest testing executable (HYPHYGTEST)

Example (MPI build of hyphy using openMPI)

Ensure that you have openmpi installed and available on your path. You can check if this is the case after running cmake . you should see something similar to this in your output

-- Found MPI_C: /opt/scyld/openmpi/1.6.3/gnu/lib/libmpi.so;/usr/lib64/libibverbs.so;/usr/lib64/libdat.so;/usr/lib64/librt.so;/usr/lib64/libnsl.so;/usr/lib64/libutil.so;/usr/lib64/libm.so;/usr/lib64/libtorque.so;/usr/lib64/libm.so;/usr/lib64/libnuma.so;/usr/lib64/librt.so;/usr/lib64/libnsl.so;/usr/lib64/libutil.so;/usr/lib64/libm.so

-- Found MPI_CXX: /opt/scyld/openmpi/1.6.3/gnu/lib/libmpi_cxx.so;/opt/scyld/openmpi/1.6.3/gnu/lib/libmpi.so;/usr/lib64/libibverbs.so;/usr/lib64/libdat.so;/usr/lib64/librt.so;/usr/lib64/libnsl.so;/usr/lib64/libutil.so;/usr/lib64/libm.so;/usr/lib64/libtorque.so;/usr/lib64/libm.so;/usr/lib64/libnuma.so;/usr/lib64/librt.so;/usr/lib64/libnsl.so;/usr/lib64/libutil.so;/usr/lib64/libm.so

Then run

make HYPHYMPI

And then run make install to install the software

make install

  • hyphy will be installed at /location/of/choice/bin
  • libhyphy_mp.(so/dylib/dll) will be installed at /location/of/choice/lib
  • HyPhy's standard library of batchfiles will go into /location/of/choice/lib/hyphy

WebAssembly Build

HyPhy provides WebAssembly builds that can run in modern browsers without installation.

Using Pre-built WebAssembly Files

The latest WebAssembly build can be downloaded from the GitHub Actions artifacts. Go to the GitHub Actions page, select the most recent successful workflow run, and download the hyphy-wasm artifact. The artifact contains:

hyphy.js hyphy.wasm hyphy.data hyphy_resources.tar.gz

Extract the resources tarball (hyphy_resources.tar.gz) in the same directory as the other files. All files should be served from the same directory on your web server. For an example of HyPhy running in the browser, see https://observablehq.com/@spond/hyphy-biowasm.

Building WebAssembly Files Locally

To build the WebAssembly files yourself, you'll need Emscripten.

  1. Configure the build - note that we don't use preload flags during configuration to avoid CMake test issues: emcmake cmake -DCMAKE_EXE_LINKER_FLAGS="-sTOTAL_STACK=2097152 -O2 -sASSERTIONS=1 -sMODULARIZE=1 -sALLOW_MEMORY_GROWTH -sFORCE_FILESYSTEM=1 -sEXIT_RUNTIME=0 -s EXPORTED_RUNTIME_METHODS=[\"callMain\",\"FS\",\"PROXYFS\",\"WORKERFS\",\"UTF8ToString\",\"getValue\",\"AsciiToString\"] -lworkerfs.js -lproxyfs.js -s INVOKE_RUN=0 -s ENVIRONMENT=\"web,worker\" ${EM_FLAGS//-s /-s} -fwasm-exceptions"

  2. Build the target: emmake make -j hyphy

  3. This will create the following files: hyphy.js hyphy.wasm hyphy.data

  4. You'll also need to copy the resource files to serve alongside the WebAssembly files: mkdir -p hyphy_resources cp -r res hyphy_resources/ cp -r tests/hbltests hyphy_resources/tests

  5. All files should be served from the same directory on your web server.

Testing

Use make test after running cmake ..

Benchmarks for CMake Tests

Benchmarks, using Github Actions, can be found at http://hyphy.org/bench

Executable Location

By default, HyPhy installs into /usr/local but it can be installed on any location of your system by providing an installation prefix

cmake -DCMAKE_INSTALL_PREFIX:PATH=/location/of/choice

For example, this configuration will install hyphy at /opt/hyphy

mkdir -p /opt/hyphy

cmake -DCMAKE_INSTALL_PREFIX:PATH=/opt/hyphy .

Building Documentation

make docs cd docs python3 -m http.server

CLI notes

As noted in the documentation here hyphy can be run as a command line tool. Indeed for many analyses the hyphy CLI will return useful help messages, showing which parameter values can be set to specify your analysis. For example, running hyphy gard --help

```{bash} hyphy gard --help

Available analysis command line options

Use --option VALUE syntax to invoke If a [reqired] option is not provided on the command line, the analysis will prompt for its value [conditionally required] options may or not be required based on the values of other options

type The type of data to perform screening on default value: nucleotide

code Genetic code to use (for codon alignments) default value: Universal applies to: Choose Genetic Code

alignment [required] Sequence alignment to screen for recombination

model The substitution model to use default value: JTT

rv Site to site rate variation default value: None

max-breakpoints Maximum number of breakpoints to consider default value: 10000

rate-classes How many site rate classes to use default value: 4

output Write the resulting JSON to this file (default is to save to the same path as the alignment file + 'GARD.json') default value: gard.defaultJsonFilePath [computed at run time]

mode Run mode (Normal or Faster) default value: Normal

output-lf Write the best fitting HyPhy analysis snapshot to (default is to save to the same path as the alignment file + 'best-gard') default value: gard.defaultFitFilePath [computed at run time] ```

will show you the options that can be set for the gard analysis. So for instance one could specify a gard run on the command line with the following command

{bash} hyphy gard --alignment /path/to/file --rv GDD --mode Faster --rate-classes 3

While this is a useful feature, it is not always the case that older analyses will have the same level of support for command line. For instance, the acd analysis does not have CLI support and so if one runs the help command

```{bash} hyphy acd --help

Available analysis command line options

Use --option VALUE syntax to invoke If a [reqired] option is not provided on the command line, the analysis will prompt for its value [conditionally required] options may or not be required based on the values of other options

No annotated keyword arguments are available for this analysis ```

one will see that there are no options available. In this case, you can use a different CLI specification. Indeed the CLI will accept all of the options that are asked for in an interactive session, as positional arguments. In this case I could run the acd analysis with

```{bash} hyphy acd Universal MG94CUSTOMCF3X4 Global 012345 Estimate

```

where the options are specified in the exact order that they are asked for in the interactive session. This will work for all hyphy analyses and provides a less readable but more flexible way to run hyphy analyses.

Owner

  • Name: iGEM/UCSD evolutionary biology and bioinformatics group
  • Login: veg
  • Kind: organization
  • Location: Philadelphia

GitHub Events

Total
  • Create event: 24
  • Release event: 12
  • Issues event: 193
  • Watch event: 25
  • Delete event: 5
  • Issue comment event: 440
  • Push event: 77
  • Pull request review event: 2
  • Pull request review comment event: 5
  • Pull request event: 67
  • Fork event: 2
Last Year
  • Create event: 24
  • Release event: 12
  • Issues event: 193
  • Watch event: 25
  • Delete event: 5
  • Issue comment event: 440
  • Push event: 77
  • Pull request review event: 2
  • Pull request review comment event: 5
  • Pull request event: 67
  • Fork event: 2

Committers

Last synced: 9 months ago

All Time
  • Total Commits: 3,161
  • Total Committers: 38
  • Avg Commits per committer: 83.184
  • Development Distribution Score (DDS): 0.321
Past Year
  • Commits: 52
  • Committers: 5
  • Avg Commits per committer: 10.4
  • Development Distribution Score (DDS): 0.423
Top Committers
Name Email Commits
Sergei L Kosakovsky Pond s****d@u****u 2,147
Steven Weaver s****r@t****u 327
rdvelazquez r****1@t****u 145
Stephanie J. Spielman s****n@g****m 134
Lance Hepler n****r@g****m 91
Art Poon a****n@g****m 68
Kevin Levitz k****n@k****m 68
sadie s****s@n****u 48
Wayne Delport w****t@u****u 42
Stephen Shank s****4@g****m 11
Dave B d****e@b****u 9
Joseph Mingrone j****m@f****a 8
Sergei L Kosakovsky Pond s****i@P****l 8
Martin Smith m****s@g****m 6
Hannah Verdonk v****h@g****m 5
Steven Weaver s****r@s****) 5
Martin Smith m****h@u****u 4
Danielle Callan d****2@g****m 4
Stephanie J. Spielman s****n@r****u 3
Stephanie s****n@t****u 3
Sergei s****i@o****u 3
George Githinji b****d@g****m 2
Sergei Kosakovsky Pond s****i@S****e 2
sweaver s****r@s****) 2
Ravi Patel r****l@t****u 2
Cornelius Roemer c****r@g****m 2
Sergei Pond s****i@s****) 1
Daisuke Fujimura (fd0) b****l@g****m 1
Sergei L Kosakovsky Pond s****i@f****u 1
Sergei L Kosakovsky Pond s****i@S****l 1
and 8 more...

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 317
  • Total pull requests: 87
  • Average time to close issues: about 2 months
  • Average time to close pull requests: 4 days
  • Total issue authors: 211
  • Total pull request authors: 10
  • Average comments per issue: 3.92
  • Average comments per pull request: 0.76
  • Merged pull requests: 68
  • Bot issues: 0
  • Bot pull requests: 1
Past Year
  • Issues: 106
  • Pull requests: 54
  • Average time to close issues: about 1 month
  • Average time to close pull requests: 1 day
  • Issue authors: 71
  • Pull request authors: 6
  • Average comments per issue: 1.97
  • Average comments per pull request: 0.78
  • Merged pull requests: 39
  • Bot issues: 0
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Top Authors
Issue Authors
  • T-164321 (8)
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Pull Request Authors
  • spond (45)
  • stevenweaver (22)
  • hverdonk (7)
  • corneliusroemer (6)
  • d-callan (2)
  • andrewkern (1)
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Packages

  • Total packages: 2
  • Total downloads:
    • pypi 63 last-month
  • Total dependent packages: 1
    (may contain duplicates)
  • Total dependent repositories: 3
    (may contain duplicates)
  • Total versions: 12
  • Total maintainers: 1
pypi.org: hyphy-python

HyPhy package interface library

  • Versions: 10
  • Dependent Packages: 1
  • Dependent Repositories: 2
  • Downloads: 53 Last month
Rankings
Dependent packages count: 4.8%
Stargazers count: 5.1%
Forks count: 5.2%
Average: 7.5%
Downloads: 10.8%
Dependent repos count: 11.6%
Maintainers (1)
veg
Last synced: 6 months ago
pypi.org: hyphy

HyPhy package interface library

  • Versions: 2
  • Dependent Packages: 0
  • Dependent Repositories: 1
  • Downloads: 10 Last month
Rankings
Stargazers count: 5.1%
Forks count: 5.2%
Dependent packages count: 10.1%
Dependent repos count: 21.6%
Average: 26.1%
Downloads: 88.3%
Maintainers (1)
veg
Last synced: 6 months ago

Dependencies

.github/workflows/benchmark.yml actions
  • actions/checkout v2 composite
  • actions/setup-node v1 composite
  • veg/github-action-benchmark v1 composite
.github/workflows/codeql.yml actions
  • actions/checkout v3 composite
  • github/codeql-action/analyze v2 composite
  • github/codeql-action/autobuild v2 composite
  • github/codeql-action/init v2 composite
.github/workflows/coverage.yml actions
  • actions/checkout v2 composite
  • actions/setup-python v1 composite
  • conda-incubator/setup-miniconda v2 composite
.github/workflows/stale.yml actions
  • actions/stale v1 composite
src/lib/setup.py pypi