phyluce uses a number of tools that allow it to assemble data, search for UCE loci, align results reads, manipulate alignments, prepare alignments for analysis, etc. To accomplish these goals, phyluce uses wrappers around a number of programs that do each of these tasks (sometimes phyluce can use several different programs that accomplish the same task in different ways). As a result, the dependency chain , or the programs that phyluce requires to run, is reasonably complex.

In previous versions (< 1.4.x), we required users to install a number of different software packages, get those into the user’s $PATH, cross their fingers, and hope that everything ran smoothly (it usually did not).

In the current versions (> 1.4.x), we have removed a number of dependencies, and we very strongly suggest that users install phyluce using either the anaconda or miniconda Python distributions, along with bioconda.


We do not support installing phyluce through means other than the conda installer. This means that we do not test phyluce against any binaries, other than those we build and distribute through conda. You will eventually be able to configure phyluce to use binaries of different provenance, although this will not be officically supported, other than providing a mechanism to do so.


We build and test the binaries available through conda using 64-bit operating systems that include:

  • Apple OSX 10.9.x
  • CentOS 6.x, 7.x
  • Ubuntu 14.04 LTS

Why conda?

It may seem odd to impose a particular disitribution on users, and we largely agree. However, conda makes it very easy for us to distribute both Python and non-Python packages (e.g. velvet, ABySS, etc.), setup identical environments across very heterogenous platforms (linux, osx), make sure all the $PATHs are correct, and have things run largely as expected. Using conda has several other benefits, including environment separation similar to virtualenv. In short, using conda gets us as close to a “one-click” install that we will probably ever get.

Install Process


We do not support phyluce on Windows.


We build and test the binaries available through conda using 64-bit operating systems that include:

  • Apple OSX 10.9.x
  • CentOS 6.x, 7.x
  • Ubuntu 14.04 LTS

The installation process is a 3-step process. You need to:

  1. Install conda (either anaconda or miniconda)
  2. Edit your ~/.condarc to add the necessary bioconda repositories
  3. Install phyluce

Installing phyluce will install all of the required binaries, libraries, and Python dependencies.

Install Anaconda or miniconda

First, you need to install anaconda or miniconda with Python 2.7. Whether you choose miniconda or anaconda is up to you, your needs, how much disk space you have, and if you are on a fast/slow connection.


You can easily install anaconda or miniconda in your $HOME, although you should be aware that this setup can sometimes cause problems in cluster-computing situations.


Do I want anaconda or miniconda?

The major difference between the two python distributions is that anaconda comes with many, many packages pre-installed, while miniconda comes with almost zero packages pre-installed. As such, the beginning anaconda distribution is roughly 200-500 MB in size while the beginning miniconda distribution is 15-30 MB in size.

We suggest that you install miniconda.


What version of miniconda or anaconda do I need?

Right now, phyluce only runs with Python 2.7. This means that you need to install a version of miniconda or anaconda that uses Python 2.7. The easiest way to do this is to choose carefully when you download a particular distribution for your OS (be sure to choose the Python 2.7 version).


Follow the instructions here for your platform:


Once you have installed either Miniconda or Anaconda, we will refer to the install as conda throughout the remainder of this documentation.


Follow the instructions here for your platform:


Once you have installed either Miniconda or Anaconda, we will refer to the install as conda throughout the remainder of this documentation.

Checking your $PATH

Regardless of whether you install miniconda or anaconda, you need to check that you’ve installed the package correctly. To ensure that the correct location for anaconda or miniconda are added to your $PATH (this occurs automatically on the $BASH shell), run the following:

$ python -V

The output should look similar to (x will be replaced by a version):

Python 2.7.x :: Anaconda x.x.x (x86_64)

Notice that the output shows we’re using the Anaconda x.x.x version of Python. If you do not see the expected output (or something similar), then you likely need to edit your $PATH variable to add anaconda or miniconda.

The easiest way to edit your path, if needed is to open ~/.bashrc with a text editor (if you are using ZSH, this will be ~/.zshrc) and add, as the last line:

export PATH=$HOME/path/to/conda/bin:$PATH

where $HOME/path/to/conda/bin is the location of anaconda/miniconda on your system (usually $HOME/anaconda/bin or $HOME/miniconda/bin).


If you have previously set your $PYTHONPATH elsewhere in your configuration, it may cause problems with your anaconda or miniconda installation of phyluce. The solution is to remove the offending library (-ies) from your $PYTHONPATH.

Add the necessary bioconda repositories to conda

You need to add the location of the bioconda repositories to your conda installation. To do that, you can follow the instructions at the bioconda site or you can simply edit your ~/.condarc file to look like:

  - defaults
  - conda-forge
  - bioconda

Once you do this, you have access to all of the packages installed at bioconda and conda-forge. The order of this file is important - conda will first search in it’s default repositories for package, then it will check conda-forge, finally it will check bioconda.

How to install phyluce

You now have two options for installing phyluce. You can install phyluce in what is known as a conda environment, which lets you keep code for different applications separated into different environments. We suggest this route.

You can also install all of the phyluce code and dependencies in your default conda environment.

Install phyluce in it’s own conda environment

We can install everything that we need for phyluce in it’s own environment by running:

conda create --name phyluce phyluce

This will create an environment named phyluce, then download and install everything you need to run phyluce into this phyluce conda environment. To use this phyluce environment, you must run:

source activate phyluce

To stop using this phyluce environment, you must run:

source deactivate

Install phyluce in the default conda environment

We can simply install everything that we need in our default conda environment, as well. In some ways, this is easier, but it could be viewed as a less-ideal option in terms of repeatability and separability of functions. To install phyluce in the default environment, after making sure that you have miniconda or anaconda in your $PATH, and after adding the bioconda repositories, run:

conda install phyluce

If you need GATK

GATK changed its licensing policies, which means that there are some extra steps you need to take to install GATK alongside phyluce. First, follow this link to download GATK 3.5. Once that is downloaded, you need to unzip/expand the archive, and GenomeAnalysisTK.jar will be inside. To install this, run the follwing:

# if phyluce is installed in its own environment (if not, skip this)
source activate phyluce

# install GATK
gatk-register /path/to/GenomeAnalysisTK-3.5-0-g36282e4/GenomeAnalysisTK.jar

That should take care of everything you need, and you should be able to run GATK on the command-line.

What conda installs

When you install phyluce, it specifies a number of dependencies that it needs to run. conda is great because it will pull specific versions of the required programs from the bioconda repository and install those on your machine, setup the paths, etc.

Below is a list of what phyluce currently (1.6.2) installs:

3rd-party dependencies and packages installed

- python
- abyss 1.5.2
- bcftools
- bedtools
- biopython
- bwa
- bx-python
- dendropy 3.12.3
- gblocks
- lastz
- mafft
- muscle
- pandas
- picard
- pysam
- pyvcf
- raxml
- samtools
- seqtk
- trimal
- trinity # [not osx]
- velvet
- illumiprocessor
- spades
- itero

Added benefits

An added benefit of using conda and installing packages in this way is that you can also run all of the 3rd-party binaries without worrying about setting the correct $PATH, etc.

For example, phyluce requires MUSCLE for installation, and MUSCLE was installed by conda as a dependency of phyluce. Because $HOME/anaconda/bin (which we will now call $CONDA) is part of our path now, and because phyluce installed MUSCLE, we can also just run MUSCLE on the command-line, with:

$ muscle

MUSCLE v3.8.31 by Robert C. Edgar
This software is donated to the public domain.
Please cite: Edgar, R.C. Nucleic Acids Res 32(5), 1792-97.

Basic usage

    muscle -in <inputfile> -out <outputfile>

Common options (for a complete list please see the User Guide):

    -in <inputfile>    Input file in FASTA format (default stdin)
    -out <outputfile>  Output alignment in FASTA format (default stdout)
    -diags             Find diagonals (faster for similar sequences)
    -maxiters <n>      Maximum number of iterations (integer, default 16)
    -maxhours <h>      Maximum time to iterate in hours (default no limit)
    -html              Write output in HTML format (default FASTA)
    -msf               Write output in GCG MSF format (default FASTA)
    -clw               Write output in CLUSTALW format (default FASTA)
    -clwstrict         As -clw, with 'CLUSTAL W (1.81)' header
    -log[a] <logfile>  Log to file (append if -loga, overwrite if -log)
    -quiet             Do not write progress messages to stderr
    -version           Display version information and exit

Without refinement (very fast, avg accuracy similar to T-Coffee): -maxiters 2
Fastest possible (amino acids): -maxiters 1 -diags -sv -distance1 kbit20_3
Fastest possible (nucleotides): -maxiters 1 -diags

This is true for other binaries you install from our repository (e.g. velveth, velvetg, abyss-pe, mafft) or any other conda repository - those binaries are all stored in $CONDA/bin.

$PATH configuration

As of v1.5, phyluce uses a configuration file to keep track of paths to relvant binaries, as well as some configuration information. This file is located at $CONDA/config/phyluce.conf. Although you can edit this file directly, you can also create a user-specific configuration file at ~/.phyluce.conf (note the preceding dot), which will override the default values with different paths.

So, if you need to use a slightly different binary or you want to experiment with new binaries (e.g. for assembly), then you can change the paths in this file rather than deal with hard-coded paths.


You do NOT need to to anything with this file - $PATHs should automatically resolve.


Changing the $PATHs in the config file can break things pretty substantially, so please use with caution (and edit the copy at ~/.phyluce.conf) rather than the default copy.

The format of the config file as of v1.6 looks like the following:


#    Advanced




Other useful tools

You will need to be familiar with the command-line/terminal, and it helps to have a decent text editor for your platform. Here are some suggestions: