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Statistical multi-Omics UNDerstanding of Patient Samples

Statistical multi-Omics UNDerstanding of Patient Samples

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.

Coordinator

EUROPEAN MOLECULAR BIOLOGY LABORATORY

Address

Meyerhofstrasse 1
69117 Heidelberg

Germany

Activity type

Research Organisations

EU Contribution

€ 650 403,75

Participants (12)

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FRED HUTCHINSON CANCER RESEARCH CENTER NON PROFIT CORPORATION

United States

EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH

Switzerland

THE CHANCELLOR MASTERS AND SCHOLARS OF THE UNIVERSITY OF CAMBRIDGE

United Kingdom

EU Contribution

€ 323 261,25

LUDWIG-MAXIMILIANS-UNIVERSITAET MUENCHEN

Germany

EU Contribution

€ 38 179,45

INSTITUTO DE ENGENHARIA MECANICA

Portugal

EU Contribution

€ 315 928,75

BEDATADRIVEN BV

Netherlands

EU Contribution

€ 318 750

UNIVERSITATSKLINIKUM HEIDELBERG

Germany

UNIVERSITAT ZURICH

Switzerland

KLINIKUM RECHTS DER ISAR DER TECHNISCHEN UNIVERSITAT MUNCHEN

Germany

EU Contribution

€ 331 000

TECHNISCHE UNIVERSITAET MUENCHEN

Germany

EU Contribution

€ 274 570,55

HEALTH RESEARCH INC

United States

EU Contribution

€ 399 593,75

DEUTSCHES KREBSFORSCHUNGSZENTRUM HEIDELBERG

Germany

EU Contribution

€ 301 375

Project information

Grant agreement ID: 633974

Status

Closed project

  • Start date

    1 September 2015

  • End date

    31 August 2018

Funded under:

H2020-EU.3.1.6.

  • Overall budget:

    € 3 656 977,50

  • EU contribution

    € 2 953 062,50

Coordinated by:

EUROPEAN MOLECULAR BIOLOGY LABORATORY

Germany