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BMC Genetics  2012 

EggLib: processing, analysis and simulation tools for population genetics and genomics

DOI: 10.1186/1471-2156-13-27

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Abstract:

In this context, we present EggLib (Evolutionary Genetics and Genomics Library), a flexible and powerful C++/Python software package providing efficient and easy to use computational tools for sequence data management and extensive population genetic analyses on nucleotide sequence data. EggLib is a multifaceted project involving several integrated modules: an underlying computationally efficient C++ library (which can be used independently in pure C++ applications); two C++ programs; a Python package providing, among other features, a high level Python interface to the C++ library; and the egglib script which provides direct access to pre-programmed Python applications.EggLib has been designed aiming to be both efficient and easy to use. A wide array of methods are implemented, including file format conversion, sequence alignment edition, coalescent simulations, neutrality tests and estimation of demographic parameters by Approximate Bayesian Computation (ABC). Classes implementing different demographic scenarios for ABC analyses can easily be developed by the user and included to the package. EggLib source code is distributed freely under the GNU General Public License (GPL) from its website http://egglib.sourceforge.net/ webcite where a full documentation and a manual can also be found and downloaded.The exponential growth of sequence databases and the advent of powerful and cost-efficient sequencing technologies have boosted the field of molecular population genetics, providing researchers with an unprecedented and ever growing amount of data [1]. Computing resources appear to be frequently limiting, complicating or even preventing the application of certain analytical methods. To overcome such limitations, automated analysis procedures and efficient computational tools are required.Although a number of programs and pieces of software implement various tasks routinely performed by population geneticists, few stand-alone packages or libraries gather together a la

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