Plant biotechnologies company Biogemma has selected Tibco Spotfire 3.1 to move beyond transcriptomic analyses and embark on new types of integrative research based on genetic maps.
As part of Biogemma's overall plan to develop a way of searching all data produced by the company's various platforms, Biogemma's first objective was to centralise data from outside projects, projects in collaboration with public or private partners, or data available in the public domain generally published in scientific articles.
This data must be integrated and formatted before it can be used; however, the flexibility of Spotfire allowed Biogemma's researchers to get around this problem and to work with heterogeneous data.
They quickly create links between the data produced internally and all other data from various sources and can produce an accurate and efficient analytical view of their research.
The principal users of Spotfire are members of the Genediscovery team, engineers and PhDs who conduct 'in silico' analyses by integrating and comparing data from the services platforms in order to discover the most effective genes for improving plants in an agricultural context.
In addition to this team, other researchers and project managers use Spotfire, for instance to visualise analyses of research into similarities between DNA sequences or when they wish to add more of a reporting dimension to the analyses.
These Biogemma researchers work in several areas of research and on four main types of crops: corn, wheat, sunflower and oilseed rape.
Their approach aims to improve these species in order to better meet farmers' requirements.
Their principal research entails identifying the genes that encourage the growth of plants adapted to the various growing locations based on: climate constraints such as cold and drought; biological constraints (presence of insects, mushrooms, parasites), regulatory constraints (decrease in pesticide inputs) and environmental constraints (reduction of fertiliser and water inputs).
Spotfire allows users to quickly identify favourable genes among the natural biodiversity of these plants.
This identification occurs through using genetic maps, by association genetics and by using all the genomic or expressed sequences and, of course, the genomic sequence of the species of interest or of related species when they are available.
Although the process of genetic map creation has now been fully mastered, the various statistics modules available in the Spotfire software make it possible to manipulate the data positioned on the genetic maps and to add information and essential research elements.
According to Biogemma, Spotfire's ease of use makes it a tool that is intuitive to use and versatile in the functions that it can perform.
It also provides the capability to perform different visualisations in both genetics and genomics, and its ability to connect to very diverse data sources such as databases and flat files is a bonus.
In addition, Biogemma's engineers are aware of the explosion in new technologies, since one of the key aspects in the field of life sciences is sequencing activities which require the retrieval of massive amounts of data - nearly one terabyte every two months - from different sites in order to carry out more complex analyses.
Spotfire has the capability to create simple visualisations, but also to launch analyses with complex statistical analysis scripts, particularly by using the R language.
The data and the analyses can therefore be handled by remote computation servers, with the final results processed using the Spotfire software.
Biogemma's teams must handle data which come from very different sources and which have been obtained using different approaches, different methods, different visions and different specialities.
The company works with researchers who analyse the contents of proteins or amino acids in seeds and with others who measure soil characteristics under conditions of drought or plant height.
Spotfire gives Biogemma's researchers a data-mining tool that is flexible enough to tolerate heterogeneity in terms of data types; added to that are all the very advanced visualisation aspects, which offers them quite exceptional statistics report performance.
