Objective
Bioinformatic analysis is the biggest bottleneck in many genomic medicine projects. Our objective is to enable researchers to dramatically increase statistically informed use of personal multi-omic data in medicine. Soon, multiple types of omic technologies will be applied to 100,000s of patient-derived samples, with the three-stage goal of better understanding disease biology, discovery of new interventions, and personalizing the choice of treatment options. Our interdisciplinary team of biostatisticians, bioinformaticians, software developers and physician-scientists will address the analysis bottleneck with statistically and computationally sound methods. The SOUND consortium will (i) develop widely used and excellent bioinformatic and statistical methods and open source software for common but challenging tasks, including data pre-processing, data integration, statistical inference, visual presentation, and publication-quality reporting; (ii) introduce novel approaches to ground breaking multi-omics applications in oncology and medical genetics; (iii) develop interoperable data structures and software interfaces that enable seamless combination of tools; (iv) support a collaborative international academic and industry developer community; (v) enable rapid development and execution of high-quality software; (vi) lower the barrier to entry into this transdisciplinary field by providing simple, robust, easy-to-use solutions; and (vii) develop a training programme with regular courses and comprehensive online tutorials. Our aim is to create the de facto standard toolkit used in every clinical research lab for statistically informed analysis of personal multi-omic data. SOUND will increase research and innovation opportunities by reducing barriers of entry to genomic medicine across academic, healthcare and commercial sectors by translating in a rapid and efficient manner complex and innovative analytical approaches into modular, interoperable, reusable applications.
Fields of science
- natural sciencescomputer and information sciencesdata sciencebig data
- natural sciencescomputer and information sciencessoftwaresoftware applicationssystem software
- natural sciencesbiological sciencesgeneticsmutation
- natural sciencesbiological sciencesgeneticsnucleotides
- natural sciencesmathematicsapplied mathematicsmathematical model
Programme(s)
Funding Scheme
RIA - Research and Innovation actionCoordinator
69117 Heidelberg
Germany
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Participants (12)
Participation ended
98109 Seattle Wa
8092 Zuerich
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CB2 1TN Cambridge
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Participation ended
80539 Muenchen
1049 001 Lisboa
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2516 BE S Gravenhage
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
Participation ended
69120 Heidelberg
8006 Zurich
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81675 Muenchen
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80333 Muenchen
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14263 Buffalo
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69120 Heidelberg
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