Getting started

TractoR can be downloaded directly from this web site, or else cloned from GitHub using git. This page outlines the process of installing the package on different platforms.

System requirements

In its basic form, TractoR is a set of packages written for the R language and environment. R (version 3.0.0 or later) is therefore an absolute prerequisite. R is an open-source package that is easy to install. Precompiled binaries are available from a number of CRAN mirror sites, along with the source code.

A C/C++ compiler, such as gcc/g++ or clang/clang++, is also required to install TractoR, although R handles all the details of actually compiling code.

Installation on Linux

Firstly, ensure that R and a C/C++ compiler are installed. It should be possible to do this using your distribution’s package manager (aptitude, yum, etc.). For example, on Ubuntu,

sudo apt-get install r-base-dev

should install everything required to build R packages. More specific information for various Linux distributions is available from CRAN.

After downloading the TractoR tarball, installing the R packages should then just be a matter of typing the following into a terminal.

tar -xzf tractor.tar.gz
cd tractor
make install

In most cases the installer will find R without any help, but if an error message reports “command not found” or similar, then please use make install R=/path/to/R, replacing /path/to/R with the actual path on your system. TractoR installs R packages into a library within its own directory structure, so it will not interfere with any other versions of those packages that you may have installed.

Unless you want to interact with TractoR exclusively through R (which is unlikely in most cases), you will also need to set up your environment so that you can use the tractor shell program and associated script files. To do this—assuming you use the bash shell—add the following lines to the .bashrc file in your home directory:

export TRACTOR_HOME=/usr/local/tractor
export PATH=${TRACTOR_HOME}/bin:$PATH
export MANPATH=${TRACTOR_HOME}/share/man:$MANPATH

Of course, if you have unpacked the tarball somewhere other than /usr/local/tractor, you will need to alter the first line accordingly.

Installation on macOS

The simplest way to install TractoR on macOS is to use the Homebrew package manager, support for which was added in TractoR version 3.1.0. Note, however, that the CRAN build of R may not be compatible with Homebrew, so if you have already installed R from CRAN, it may be better to follow the instructions in the next paragraph. Once Homebrew itself is installed, the command

brew install tractor/tractor/tractor

should suffice to install R, TractoR and the necessary compilers. In this case the TRACTOR_HOME environment variable should generally be set to /usr/local/opt/tractor. Homebrew also makes it easy to update to new releases of R and TractoR later on.

The alternative is to install R from CRAN, in which case you may also need to obtain the compilers used for the CRAN build. Apple’s own developer tools can be installed using the command

xcode-select --install

but at the time of writing this is not sufficient to build TractoR against R from CRAN. Either way, once R is installed, you should download the TractoR tarball, uncompress it, run make install and set up the environment as described in the instructions for Linux above.

Installation on Windows

TractoR was developed for Unix-like systems, but installation and use on Windows is possible. If you are running Windows 10, the best route might be to install the recently introduced Windows Subsystem for Linux, and then install TractoR as if on Linux. Step-by-step instructions are available for this route.

The second option is to use the Docker containerisation system. A Docker container for the TractoR minor version you want can be downloaded and launched using commands like

docker pull jonclayden/tractor:3.1
docker run -it --rm jonclayden/tractor:3.1

This will drop you into a bash shell in a Linux-based container with R and TractoR already installed and set up for you. You can consult Docker’s documentation for more information on giving the container access to your data.

The final and most heavyweight option is to run a full Linux distribution within a virtual machine environment such as VirtualBox or VMware, and then proceed as described above for Linux. FSL’s developers provide a virtual machine image which may be suitable.

Checking your installation

To check that the TractoR packages have been installed properly and TractoR scripts can be run successfully, you can run the set of tests included with TractoR 1.3.0 and later by typing

make clean test

Running these tests will typically take a few minutes, during which time you should see a series of messages confirming the success of each test, and the run time in each case. If any errors arise, something is probably wrong with your installation.

To test that the environment is set up correctly, try typing

tractor list

which should produce output similar to the following:

DICOM handling:
  age, dicomread, dicomsort, dicomtags

Image processing:
  binarise, components, morph, smooth, trim

General analysis:
  apply, extract, imageinfo, imagestats, mean, mkroi, reshape, values

Visualisation:
  slice, view

Registration:
  reg-apply, reg-check, reg-info, reg-linear, reg-nonlinear, reg-viz

Working with sessions:
  clone, import, status, transform

Diffusion processing:
  bedpost, dirviz, dpreproc, gradcheck, gradread, gradrotate, plotcorrections, 
tensorfit, track, trkinfo, trkmap

Structural processing:
  deface, freesurf, parcellate

Heuristic neighbourhood tractography (deprecated):
  hnt-eval, hnt-interpret, hnt-ref, hnt-viz

Probabilistic neighbourhood tractography:
  pnt-data, pnt-em, pnt-eval, pnt-interpret, pnt-prune, pnt-ref, pnt-sample, 
pnt-train, pnt-viz

Graph and network analysis:
  graph-build, graph-decompose, graph-extract, graph-props, graph-reweight, 
graph-viz, graph2csv

Other scripts:
  chfiletype, compress, console, list, path, peek, platform, split, update

For information on a particular script, run "tractor -o <script>"

If instead you get an error from the shell saying that it couldn’t find the tractor executable, or from tractor itself reporting the script file not found, the installation has not been completed correctly. Check that you have set up your environment as shown above, and make sure that you have started a new shell or sourced your .bashrc file to pick up the changes (source ~/.bashrc). Running the command man tractor should show the tractor man page.

Usage

The tractor command line interface program is a wrapper which obviates the need to interact with R directly in order to use TractoR. Many common tasks, including neighbourhood tractography (see “Next steps” below), can be performed in this way through short R scripts which are stored within the TractoR home directory.

A full list of the scripts provided with the distribution can be obtained by typing tractor list, as shown above. Further information on a particular script, including a list of options that it supports, can be obtained using tractor -o (script name). For more details on the usage of the tractor program, please see its man page (man tractor).

Next steps

It is a good idea to read a little about TractoR’s specific conventions, which will make the rest of this documentation easier to follow. After that you may wish to explore TractoR’s implementation of “neighbourhood tractography”, a robust and flexible method for consistent white matter tract segmentation in the brain.