Anduril is an open-source computational framework for the combined analysis of molecular and clinical information developed by Sampsa Hautaniemi and colleagues to allow integration of clinical information with large-scale molecular datasets such as transcriptomes, miRNA, single nucleotide polymorphisms, copy number variation and methylation data. In a recent article published in Genome Medicine they describe this tool and demonstrate its utility in an analysis of glioblastoma multiforme patient data from The Cancer Genome Atlas. 

Their analysis of molecular and clinical data from 338 glioblastoma multiforme patients suggested several novel candidate genes related to disease progression.  In particular, increased expression of the Moesin gene appeared to have a strong association with poor patient survival, and functional analyses confirmed that depletion of this gene inhibited cell proliferation, making it a good candidate for further study of this poorly-understood disease.

Anduril’s benefits include the ability to analyse heterogenous large-scale disease data to generate testable predictions for future functional studies, and may be used by scientists without bioinformatics training to interpret the increasingly complex datasets generated by current medical genomics research.