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Galaxy course EMC TraIT Nov 2014_Jenster
Data analysis and integration How to get from a pile of unprocessed data to knowledge: The user’s perspective Guido Jenster, Ph.D. Professor of Experimental Urological Oncology Department of Urology Erasmus MC
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Experimental Research
Prostate Cancer Molecular Medicine Clinical Research Biobanking Experimental Research Imaging DATA QUERY VIEWING DATA INTEGRATION DATA PROCESSING NEW KNOWLEDGE DATA STORAGE DATA GENERATION
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Prostate Cancer Molecular Medicine
What do we want? Use case: Identify novel fusion genes from DNA and RNA sequencing data PUSH TO START
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Copy Number Abberations
DNAseq Data Analysis SNVs / InDels Copy Number Abberations TF Binding B-Allele Frequency DNAseq data Chromatin Interactions Structural Variations Methylation Active Chromatin Identify Integration Sites Read Barcode
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Differential expression
RNAseq Data Analysis Differential expression SNVs / InDels RNAseq data Alternative splicing & Promoters Read-Through & Fusion Transcripts Novel Transcripts
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TraIT Galaxy
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Work Flows
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The TraIT mansion requires good support
WP4 Phenotype Database BMIA Data storage + CPU power TTP SurfConext Catalogue Open Clinica Chipster XNAT tEPIS Logis Workflow Galaxy Keosys coLIMS tranSMART TOP desk Alfresco Website Wiki Jira
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