R2: Biologist friendly web-based genomics analysis & visualization
30-3-2015 R2: Biologist friendly web-based genomics analysis & visualization platform Power to the biomedical researcher Jan Koster Department of Oncogenomics Academic Medical Center (AMC) UvA, the Netherlands [email protected] The problem • High throughput technologies have become part of the every day biomedical laboratory standards • Working with these data can be challenging and is often done via external collaboration (bioinformatics group) • As a consequence the wetlab researchers are out of touch with their own data, while external data analysts that are not in touch with the experiment are analyzing the data in stead. [email protected] SKK 2 1 30-3-2015 What is R2? • R2 genomics analysis and visualization platform – Web based (http://r2.amc.nl) • No installation required • Works everywhere (lab / home / conference room) – (Public) collection datasets • Uniform normalization – Analysis/Visualization tools • Intended users – Biomedical researchers – Wetlab biologists • Queries – Targeted by users interests – Graphical representations [email protected] SKK 3 2 30-3-2015 Overview of R2 core [email protected] SKK 5 Before we start • Neuroblastoma – Childhood tumor – MYCN oncogene amplified (++ DNA copies) in 20% patients • Bad prognosis on their survival • Amplification is measured in clinical setting and used in risk stratification • Most of the options in R2 will be demonstrated in a neuroblastoma dataset generated within the department of Oncogenomics (NB88), and in addition focus on the MYCN gene or its amplification status [email protected] SKK 6 3 30-3-2015 R2 main window [email protected] SKK 7 R2 main window [email protected] SKK 8 4 30-3-2015 R2 main window [email protected] SKK 9 View a gene [email protected] SKK 10 5 30-3-2015 View a gene [email protected] SKK 11 View a gene [email protected] SKK 12 6 30-3-2015 View a gene [email protected] SKK 13 TranscriptView [email protected] SKK 14 7 30-3-2015 Differential Expression [email protected] 15 SKK 15 Differential Expression [email protected] SKK 16 8 30-3-2015 Differential Expression [email protected] SKK 17 Detailed View [email protected] SKK 18 9 30-3-2015 Detailed View [email protected] 19 SKK 19 Detailed View [email protected] SKK 20 10 30-3-2015 KaplanScan [email protected] SKK 21 Differential Expression [email protected] SKK 22 11 30-3-2015 2 groups plotter [email protected] SKK 23 Differential Expression [email protected] SKK 24 12 30-3-2015 Gene Ontology [email protected] 25 SKK 25 Differential Expression [email protected] SKK 26 13 30-3-2015 Scavenger / gene set analysis [email protected] SKK 27 Differential Expression [email protected] SKK 28 14 30-3-2015 Also in R2 [email protected] SKK 29 Across datasets • One of the Powers of R2 is the large database of diverse (public) datasets and the possibility to combine them for analysis / visualizations Cell Lines Pediatric Cancers Normal Tissues RMS OS NRBL MB GBM Ewing Leukemia [email protected] SKK Adult Cancers 30 15 30-3-2015 Integrative Analyses (different data types) + [email protected] Hovestadt et al, Nature, 2014 SKK 31 4: Whole genome sequencing data in R2 Neuroblastoma primary tumors (n=87 pairs) Only ~12 aa affecting mutations Chromothripsis frequent in high stage disease Structural variations affecting single genes [email protected] Molenaar & Koster et al, Nature, 2012 SKK 32 16 30-3-2015 Whole genome sequencing data in R2 Cohort [email protected] SKK Patient Variants 33 R2 usage overview [email protected] SKK http://r2.amc.nl 34 17 30-3-2015 Acknowledgements Development/Concepts/Support Jan Koster Richard Volckmann Piet Molenaar Danny Zwijnenburg Jan Molenaar Marcel Kool Linda Valentijn Rogier Versteeg [email protected] SKK 35 18
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