Abstract
BackgroundWith the considerable growth of available nucleotide sequence data over the last decade, integrated and flexible analytical tools have become a necessity. In particular, in the field of population genetics, there is a strong need for automated and reliable procedures to conduct repeatable and rapid polymorphism analyses, coalescent simulations, data manipulation and estimation of demographic parameters under a variety of scenarios.ResultsIn 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.ConclusionsEggLib 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/ where a full documentation and a manual can also be found and downloaded.
Highlights
With the considerable growth of available nucleotide sequence data over the last decade, integrated and flexible analytical tools have become a necessity
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]
We present EggLib, a software package for evolutionary genetics and genomics centered on tools for population genetics analysis
Summary
With the considerable growth of available nucleotide sequence data over the last decade, integrated and flexible analytical tools have become a necessity. 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. 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 large number into a single tools should be sufficiently easy to use for nondevelopers. In this article we aim at providing the population genetics community with an efficient, flexible, easy to use and complete Python library. EggLib offers integrated tools for processing biological sequence data, analyzing nucleotide alignments, performing coalescent simulations allowing rarely featured mutation models, mutational bias as well as explicit selfing and estimating demographic parameters through ABC. We will provide an overview of the different features of the package and how it compares to existing software in terms of memory usage and running time (Results and Discussion)
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