Resources

Introduction

During the SMBE Satellite workshop on speciation genomics, we ran four practical sessions on two important software packages.

Efficient and fast simulations with msprime

The first package was msprime and a focus on how the tree sequence format is an efficient means of storing and simulating data. New developments with tskit mean that it also simpler than ever to rapidly estimate summary statistics from simulated data. You can learn more about msprime and tskit here and here. These sessions were led by Georgia Tsambos and Jerome Kelleher.

Going further with genome scans using gIMble

The second package was gIMble a tool for inferring demography and effective migration rate from genome scan data. These sessions were led by Konrad Lohse, Gertjan Bischop, Derek Setter and Dom Laetsch. You can learn more about gIMble here.

Using the resources

Even if you didn’t attend the workshop, we want the resources to be freely available to the community. There are several ways that you can use them.

Running the Jupyter notebooks using binder

The simplest way to get your hands on the resources is to use binder which will run the Jupyter notebooks we used for the workshop. Compute resources will be limited in comparison to the original run through in the workshop but you should be able to work through most of the exercises.

To run the binder based resources, go here and click on the launch binder button. Many thanks to Ariella Gladstein for making this possible.

Running the resources locally

Alternatively you can install the programmes locally and run the resources on your own machine. The best way to do this is via a conda installation but you can also install it directly using pip. See [here] (https://msprime.readthedocs.io/en/stable/installation.html) for more info.

You will also need to install tskit. This can be done via pip - see here for more info.

To install gIMble you will need a conda installation (see here if you are not yet familiar with the wonderful world of conda) and should enter the following commands:

# clone repository
git clone https://github.com/DRL/gimble.git

# create conda enviroment with dependencies
conda create -n gimble && \
source activate gimble && \
conda install -c conda-forge more-itertools tqdm scipy numpy matplotlib sympy giac networkx psutil pandas docopt pytables tabulate git htop && \
conda install -c bioconda pysam

You will also need blocktools. Again follow these commands:

# clone repository
git clone https://github.com/DRL/blocktools.git

# create conda enviroment with dependencies
conda env install -f $BLOCKTOOLS_PATH/blocktools.conda.yml

# Activate blocktools conda environment
conda activate blocktools

Finally, you will need to clone the github repository where the resources are stored. To do this, do the following:

git clone https://github.com/DRL/SMBE-SGE-2019.git

Enjoy!