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• Overview of cancer genomics field
• Common applications of HT technologies in cancer genomics
• {"title"=>"Concepts and case studies of cancer genomics from the literature", "content"=>["Cancer genetics", "Pharmacogenomics", "Diagnostic vs. prognostic markers and druggable targets"]}
• Data security and privacy

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• {"title"=>"Overview of cancer specific databases, as well genome browsing and cancer genome browsing. The databases:", "content"=>["ICGC portal, TCAG, etc.", "COSMIC, dbSNP, etc."]}
• {"title"=>"The browser tools:", "content"=>["IGV", "UCSC"]}

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• How to use the genome browsers to visualize transcripts, mutations, and other cancer genome features. Subsequent modules and lab practicals will use the same browser tools.

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• What is involved in mapping reads to a reference genome
• What are the FASTQ and SAM/BAM file formats
• Some common terminology used to describe alignments
• Fundamentals of de novo assembly
• Data structures used by assemblers (de Bruijn graphs and overlap graphs)
• Common steps that assemblers perform
• Overview of commonly used software

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• Genome alignment exercise

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• Importance of copy number alterations in cancer
• Methods for detecting copy number alterations
• Tools for evaluating CNAs in HT-seq data

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• Hands-on lab exercises using CNA caller tool for CNA detection in SNP arrays.

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• Relevance of detecting somatic mutations in cancer genomics
• Strategies for detection of somatic mutations and factors considered by SNV callers
• Binomial mixture models to model allelic counts
• Simultaneous analysis of tumor and normal data
• Sources of artifacts and false positives

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• Hands on lab exercises using SNV calling tools for somatic mutation detection

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• Role of gene expression profiles in the cancer continuum
• {"title"=>"The Technology Platform: High-throughput sequencing", "content"=>["Variety of platforms and their differences", "Experimental design considerations", "Limitations of experiments"]}
• {"title"=>"The Analysis Tools:", "content"=>["Outline of a RNA-Seq analysis pipeline", "Tools for analysis of RNA-Seq data"]}

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• Analysis of RNA-Seq data.

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• Genomic rearrangement and its effect on the transcriptome
• Biological relevance of gene fusions in cancer biology
• {"title"=>"The technology platform: RNA-Seq", "content"=>["Overview of the RNA-Seq protocol", "Experimental design considerations"]}
• {"title"=>"The analysis tools:", "content"=>[{"title"=>"Alignment based fusion discovery", "content"=>["Paired end RNA-Seq alignments and gene fusion evidence", "Discerning true fusions from artifacts"]}, {"title"=>"Assembly based fusion discovery", "content"=>["Benefits/drawbacks of assembly methods", "Identifying gene fusions from RNA-Seq assemblies"]}]}
• Clinical applications

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• Hands on exercise using deFuse to identify fusions. Visualize RNA-Seq fusion reads in IGV, plot exon expression of fused genes, and use the ucsc genome browser view fusions in tandem with other genomic features.

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