I’ve recently been a reviewer for the book “Bioinformatics with Python cookbook” by Tiago Antao, one of the big authors of BioPython. The book is published by Packt Publishing, and it is a collection of recipes for several bioinformatics tasks, from reading large genome files to doing population genetics and other tasks.
The github account of the author contains a link of all the python notebooks illustrated in the book. These notebook are freely accessible, but there is no explanation of the code, as for that you will need to buy the book. Moreover, the book provides a link to a docker image that can be used to install all the materials and software needed to execute the examples. I think this is a smart way to provide materials for exercises, and I will copy the idea in the future.
Being a reviewer, I was expected to be an expert in all the topics described in the book. However I must admit that I learned a lot from reviewing it, and that some of the recipes presented managed to surprise me. Here is a quick summary of the new things I learned:
- How to convert many bioinformatics-related formats with pygenomics and biopython
- How to use the rest APIs for querying ensembl
- How to do and plot a PCA in python and eigensoft of SNP data
- SimuPOP is a nice software for simulating population genetics events
- DendroPy is a nice module for dealing with phyologenetic trees, like ete
- PDB files are going to be replaced by mmCIF files, and BioPython is able to read both formats
- pymol and cytoscape can be commanded from within a python script/ipython
- PSIQUIC is a consistent interface to many molecular-interaction databases
- ipython has excellent multi-core execution capacity.
- it is easy to optimize python code with cython and numba, just by adding a few decorators
If you buy the book and find any error in the code, you can blame me as I was a reviewer and didn’t find it.