SNiPlay is a flexible and user-friendly web application that rapidly explores SNP data using a wide range of analyses.
Our experiments within the grapevine genetics projects showed that SNiPlay allows geneticists to efficiently manage and analyze the large amounts of SNP data generated by high-throughput technologies and, therefore, to rapidly obtain advanced results in several key areas of plant genetic diversity research.
The major advantage of SNiPlay is that it saves considerable time by automatically detecting SNPs and indels from sequencing data and by injecting allelic data into a reliable multi-analysis system.
It presents detailed and well-organized information so that scientists can avoid routine data processing work and focus on the biological aspects of their own projects. For instance, submitting multiple datasets makes it easy to quickly identify and localize signals of positive selection with the help of diversity maps.
Currently, besides the International HapMap project  in Humans, few published databases are dedicated to SNPs and allelic data in other species. FlySNPdb  provides SNP data for the major chromosomes of Drosophila melanogaster. Recently, AutoSNPdb  has been developed to identify and store SNPs from assembled EST sequences in rice, barley and Brassica species.
With more than 1,400,000 SNP alleles at 39,163 sites, SNiPlay hosts and provides the grapevine community with a sizeable resource of polymorphisms and other genetic data, and could become the international reference as a grapevine SNP datasource. It can thus provide significant global statistical information on SNPs and indels across the grapevine genome such as density, proportion of synonymous SNPs, and heterozygosity.
SNiPlay is fully functional and currently used by multiple laboratories. Initially conceived to meet grapevine research needs, it was successfully used with grapevine Sanger sequencing data for SNP discovery and genome-wide diversity analysis and with Illumina VeraCode genotyping data for LD fine study in regions of interest. However, SNiPlay provides a generic system for SNP management designed to be applicable to sequence or allelic data of any diploid species. Indeed, the system presently manages allelic data on rice, and it is also being used for de novo transcriptome sequencing in various Coffea species.
In addition, SNiPlay is independent of the sequencing technology since it accepts standard FASTA alignments. Short reads from NGS deep sequencing experiments (454, Solexa) can make use of SNiPlay, if the assembly have been preliminarily pre-processed and formatted into FASTA alignment files including IUPAC symbols at heterozygous positions. SNiPlay, being a web application, cannot afford such a task online. However, among the further developments planned for coming years, an additional and independent module will be incorporated to pre-process the assembly of short reads from NGS technologies, by detecting SNPs using depth and quality criteria and converting assemblies into FASTA alignments. As a rule, efforts will be constantly undertaken to take into account future technologies.
The second major development planned is the addition of a new component for association studies based on the TASSEL software and/or the GenABEL library .
The modular architecture of the SNiPlay pipeline renders this system easily extensible, which will facilitate the addition of new features and programs according to user feedback. For instance, we plan to integrate another phasing program such as FastPhase  and to improve the linkage disequilibrium module.
More generally, we intend to integrate in the future new modules able to manage other types of analyses such as kinship, population structure, and phylogeny.
Finally, because SNiPlay is being accepted by the local community working on diversity projects as the tool for SNP management and analysis, it will naturally benefit from continuous maintenance and improvements. It is expected to evolve towards an open-source distribution package including both pipeline and database so that it can be locally and independently installable in multiple labs and adapted for small user communities working on different plant species.