Requirements

If you are not in sudoers, then you can still install AMO without root access. Firstly, you are required to install the dependencies step by step.

Unix-like system

sudo apt-get update
sudo apt-get install -y --no-install-recommends \
      build-essential \
      libgflags-dev \
      libgoogle-glog-dev \
      libomp-dev \
      libeigen3-dev \
      libbz2-dev \
      libhdf5-dev

Mac OSX

We highly recommend using the Homebrew package manager to install the dependencies.

brew install -vd cmake gflags glog boost
brew install zlib bzip2

Step-by-step

GCC

Sometimes, on an old UNIX-like distribution, a new version of gcc is required (i.e. utilize the features from C++11 standard) before installing other dependencies. Don't worry, here is how you can compile your own gcc on the distribution with/without root access.

Make

If the version of gcc is not too old on your distribution, you can just simply install the make as follows,

If you compile your gcc own , then you are recommanded (as shown above in step 5, just uncomment the lines) to run as follows,

Cmake

Or install cmake by following lines if you compile your own gcc

Boost library

On Unix-like system, it is easy to install Boost library with sudo, type the following command in the terminal to install Boost library.

If you would like to install the Boost library without root, you can follow this instruction to install it.

Gflags

The gflags package contains a C++ library that implements command line flags processing.

Glog

The glog library contains a C++ implementation of the Google logging module.

HDF5

AMO is only tested on HDF5 Version 1.8.14

PyTorch

More details can be found here. In AMO, we call modules in PyTorch to build deep learning models that are leveraged to analyze biological data.

Plotting

If one would like to run amo with figures, plotting packages are required to install. Gnuplot and R are two packages to generate figures.

Then, install library circlize as follows,

Install Gnuplot in the terminal as follows,

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