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Next-Generation Sequencing and Analysis of Genomes

Session Type: Methods Workshop
Session Start/End Time:         Saturday, Apr 06, 2013, 1:00 PM – 3:00 PM
Location:         Ballroom A-B, Washington Convention Center
CME:   CME-Designated
CME/CE Hours:          2

Session Description:   High-throughput sequencing has enabled applications for understanding genomic alterations and aberrant expression in human cancers. Numerous computational methods have been developed to comprehensively analyze the rapidly increasing cancer genomics data thereby maximizing the discovery, interpretation, and prioritization of critical altered genes and pathways. This session will focus on methods for transcriptome and whole genome sequence analysis by highlighting current approaches, data analysis issues, and application to cancer research.

Presentations:

Chairperson
Saturday, Apr 06, 2013, 1:00 PM – 3:00 PM
Christopher A. Maher. Washington University, Saint Louis, MO

Gene fusion discovery from using transcriptome sequencing
Saturday, Apr 06, 2013, 1:00 PM – 1:20 PM
Christopher A. Maher. Washington University, Saint Louis, MO

Discussion
Saturday, Apr 06, 2013, 1:20 PM – 1:30 PM

RNA sequencing for analyzing expression of genes and isoforms
Saturday, Apr 06, 2013, 1:30 PM – 1:50 PM
Katherine Hoadley. University of North Carolina, Chapel Hill, NC

Discussion
Saturday, Apr 06, 2013, 1:50 PM – 2:00 PM

CRAVAT: A next-generation application for cancer mutation analysis
Saturday, Apr 06, 2013, 2:00 PM – 2:20 PM
Rachel Karchin. Johns Hopkins Univ., Baltimore, MD

Discussion
Saturday, Apr 06, 2013, 2:20 PM – 2:30 PM

Network and pathway analysis of genomic aberrations in cancer
Saturday, Apr 06, 2013, 2:30 PM – 2:50 PM
Benjamin J. Raphael. Brown University, Providence,, RI

Discussion
Saturday, Apr 06, 2013, 2:50 PM – 3:00 PM

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Mikael Huss – Bioinformatics Scientist at WABI (Wallenberg Advanced Infrastructure for Bioinformatics) Science for Life Laboratory / DBB, Stockholm University – February 13, 2013

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The primary graphical interface to iPlant is the Discovery Environment (DE). The DE provides a web interface and a platform to access the computing, data storage, and analysis application resources provided by iPlant.

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Total RNA Transcript Analysis on the Ion Torrent™Platform: Insight Into Functional ncRNA in Cancer
Timothy Triche, MD, PhD
Professor, Pathology & Pediatrics, USC KSOM
Director, Center for Personalized Medicine at CHLA

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Deep sequencing of the cancer transcriptome has revealed an unexpected complexity including the presence of proteins that are unique to the cancer. As more than 60% of the genome is now believed to be transcribed, understanding the changes in the coding genes as well as the noncoding regulatory transcriptome is critical for a clear elucidation of the dysfunctional cancer genome. The RNA seq method provides a comprehensive amount of information on the cancer transcriptome: highly sensitive and accurate gene-expression levels, alternative splice forms, novel fusion transcripts, and mutational changes that have a direct impact on protein function. In this webinar, presenters will review transformative discoveries from RNA-seq, and describe a highly effective approach for isolation and characterization of circulating tumor cells using RNA-seq at single cell resolution. Parameters that affect quantification of expressed nucleotide sequence polymorphisms (SNVs) will also be discussed, as will the development and implementation of tools for the identification of fusion transcripts.

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Kasper Hansen gives an introduction to RNAseq and relevant computational and statistical issues

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Stuart M. Brown. Zuojian Tang. Center for Health Informatics & Bioinformatics. NYU School of Medicine.

For those who missed it… here are the slides from the recent short training class presented by the Bioinformatics & Research Computing group at the Whitehead Institute.

January 17, 2013 – RNA-seq Analysis in Galaxy

Hands-on 1 Quantification and assay for differential expression of reference annotation

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SeqMonk has a number of tools which make it easy to analyse complex RNA-Seq experiments containing biological replicates and multiple biological conditions. In this tutorial we show how to check the quality of your data and then perform a differential analysis across multiple conditions, splitting the results into groups of genes with similar expression profiles across your conditions, to make interpretation of the results as easy as possible.

http://www.bioinformatics.babraham.ac.uk/projects/seqmonk/

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High-Grade Serous Ovarian Adenocarcinoma Transcriptome Sequencing by Andrew J. Mungall, Ph.D. of British Columbia Cancer Agency

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RNA-seq from Isolation to Analysis.
Speaker. Fabio Raffaldi, Sr FAS Ion Torrent / SOLiD + RNA ESPOC.
Kelli Bramlett – Life/Ambion R&D.
Tom Bittick Life/AmbionProduct Management

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• SEQanswers – RNA Sequencing

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