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SomaticSeq: An Ensemble Approach with Machine Learning to Detect Cancer Variants June 16 at 1pm EDT | Register for this Webinar |  View All Webinars

Accurate detection of somatic mutations has proven to be challenging in cancer NGS analysis, due to tumor heterogeneity and cross-contamination between tumor and matched normal samples. Oftentimes, a somatic caller that performs well for one tumor may not for another.

In this webinar we will introduce SomaticSeq, a tool within the Bina Genomic Management Solution (Bina GMS) designed to boost the accuracy of somatic mutation detection with a machine learning approach. You will learn:

• Benchmarking of leading somatic callers, namely MuTect, SomaticSniper, VarScan2, JointSNVMix2, and VarDict

• Integration of such tools and how accuracy is achieved using a machine learning classifier that incorporates over 70 features with SomaticSeq

• Accuracy validation including results from the ICGC-TCGA DREAM Somatic Mutation Calling Challenge, in which Bina placed 1st in indel calling and 2nd in SNV calling in stage 5

• Creation of a new SomaticSeq classifier utilizing your own dataset

• Review of the somatic workflow within the Bina Genomic Management Solution

Speakers:

Li Tai Fang Sr. Bioinformatics Scientist Bina Technologies, Part of Roche Sequencing

Anoop Grewal Product Marketing Manager Bina Technologies, Part of Roche Sequencing

<Read full speaker bios here>

Cost: No cost!

Schedule conflict? Register now and you’ll receive a copy of the recording.

This webinar is compliments of: 

Bio-ITWorld.com/Bio-IT-Webinars