OCT 17, 2013 09:00 AM PDT

Using DNASTAR Software to Identify Cancer Variations in Targeted Resequencing Data

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  • Senior Manager, NGS Applications, DNASTAR
      Matthew Keyser is Senior Manager, NGS Applications for DNASTAR, where he has helped scientists address their sequence assembly and analysis challenges for the past seven years. Matts sole focus at DNASTAR is supporting customers in next-gen sequencing applications using DNASTARs broad software toolset. Matt helps customers with their templated and de novo assembly projects, transcriptomes, exomes, metagenomic assemblies, RNA-Seq, ChIP-Seq and numerous other unique experiments. Matt has helped hundreds of scientists optimize their workflows using DNASTARs next-gen software solutions. He has also spoken at numerous conferences and workshops regarding the capabilities of DNASTARs next-gen software tools.


    DNASTAR offers an integrated suite of software for assembling and analyzing data from all major next-generation sequencing platforms. The software supports a variety of reference guided and de novo assembly workflows, including whole genomes, transcriptomes, targeted resequencing, ChIP-Seq and miRNA. In this presentation, we will show two different assembly projects that can be completed on a desktop computer using DNASTAR software: 1) bacterial genome assembly with gap closure using a reference genome from a related organism and 2) alignment of multiple human exomes against a reference genome that includes GenBank, dbSNP, Cosmic, and GERP annotations. After each assembly, the software can be used to view depth of coverage, read alignment, and SNPs and indels. SNPs can be filtered based on a variety of factors, including impact on gene function, phenotypic and ontology data for associated genes, and presence/absence in dbSNP and other databases. In the case of multiple samples, SNPs can also be compared across samples or groups. The integration of all these tools into one software package facilitates fast, comprehensive analysis, helping scientists move quickly from raw next-gen sequencing data to meaningful results. By using innovative algorithms within the software, scientists can have all of the assembly and analysis capabilities available to them on their desktop computer. Learner Objectives: Have a better understanding of sequence assembly and analysis software More familiarity with large-scale targeted re-sequencing (exome) assembly and analysis More familiarity with RNA-Seq expression analysis

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