OCT 17, 2013 9:00 AM PDT

Using DNASTAR Software to Identify Cancer Variations in Targeted Resequencing Data

Speaker

Abstract

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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OCT 17, 2013 9:00 AM PDT

Using DNASTAR Software to Identify Cancer Variations in Targeted Resequencing Data


Specialty

Virology

Antibodies

Immunology

Dna Sequencing

Personalized Medicine

Clinical Diagnostics

Immunity

Immunotherapy

Cancer Diagnostics

Flow Cytometry

Bioinformatics

Immuno-Oncology

Gene Expression

Dna

Big Data

Geography

Europe100%

Registration Source

Website Visitors100%

Job Title

Student100%

Organization

Academic Institution100%


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