Bioinformatics with Python Cookbook - Second Edition

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The truth is that for population genetic analysis, nothing beats R; you are definitely encouraged to take a look at the existing R libraries for population genetics. Do not forget that there is a Python-R bridge, which was discussed in Chapter 1, Python and the Surrounding Software Ecology.

Most of the analysis presented here will be computationally costly if done on bigger datasets (remember that we are only using chromosome 2, subsampled at 10 percent). Chapter 9, Python for Big Genomics Datasets, will discuss ways to address this.