Cassandre is a project of personal database system, integrating a “user-friendly” interface to manage and explore multiple sets of large-scale experimental results in biology.
Large-scale experiments that generate quantitative data, such as changes in the levels of thousands of RNA or protein molecules under various conditions, are a hallmark of modern biology. Many other experiments, like those measuring functional interactions between mutant alleles or the variation in the translation status of mRNAs are also characterized by the same basic information unit: an experimental condition, a genomic feature (usually a gene) and an associated numerical value.
We propose the development of such a tool for the exploration of large-scale data. This new “window” to quantitative experimental results aims to be simple, extensible, open and based on the interactive web interface developed by the coordinator of the project for the analysis of a collection of hundreds of genome-wide genetic interaction screen results.
The objectives of our project are:
- To develop the kernel of a database managing system for large-scale datasets.
- To create and implement plugins that makes use of the best practices for data exploration, in which the scientists will be able to visualize, explore, and correlate results of various experiments and integrate such results with previous knowledge (Gene Ontology annotations and publications).
A prototype of user interface for quantitative data exploration was developed by the coordinator of the project. However, this prototype is specialized in a given type of experimental data obtained on the yeast S. cerevisiae and hardwired to a specialized database system.
The ultimate goal of our project, which goes beyond the current proposal and depends on its completion, is to enable the identification of patterns and links in experimental data that would lead to new testable hypotheses and discoveries.
The main features of this application are :
- A modern and user-friendly interface,
- Multiple ways to visualize and explore your data,
- A high degree of interaction with the generated figures,
- Almost no constraints concerning the data format
- Free and open source, under GNU general public license 3.0.