As one gains more intuitions and results on the importance of concerted activity in spike trains, models are developed to extract potential canonical principles underlying spike coding. These methods shed a new light on spike train dynamics. However, they require time and expertise to be implemented efficiently, making them hard to use in a daily basis by neuroscientists or modelers. To bridge this gap, we developed the license free multiplatform software ENAS integrating tools for spike trains analysis and simulation. These tools are accessible through a friendly Graphical User Interface that avoids any scripting or writing code from user. Most of them have been implemented to run in parallel to reduce the time and memory consumption. One of the main strength of ENAS when compared to competing software is to provide statistical analysis with Maximum Entropy-Gibbs distributions taking into account both spatial and temporal correlations as constraints, allowing to introduce causality and memory in statistics. Conversely, given this analysis or other known statistics, ENAS one can also generate new spike trains. These methods result from a series of work and they have already been applied to the analysis of retina data. This comes in addition to basic visualizations and classical analysis for statistics of spike trains analysis. All these tools are generic and can be applied to any spike train. Interestingly, ENAS also includes specific tools dedicated for vision, and the retina in particular. For example, one can jointly visualize stimulus and spiking activity or estimate receptive fields. ENAS also includes a virtual retina simulator extending former Virtual Retina simulator to include lateral connections in the IPL. We hope that ENAS will become a useful tool for neuroscientists to analyse spike trains and we hope to improve it thanks to user feedback. Our goal is to progressively enrich ENAS with the latest research results, in order to facilitate transfer of new methods to the community. It is downloadable from https://enas.inria.fr where documentation, tutorials and samples of spike trains are available.