genomize-Seq’s Confidence Classification for Variants

May 9, 2017 in White Papers
genomize-Seq is a next generation sequencing (NGS) data analysis, management and sharing platform. In this blog letter, we will explain the parameters genomize-Seq employs for variant confidence classification.
genomize-Seq uses a three-level confidence classification scheme, with the classes High, Low and Failed. (Figure 1) A parameter optimization is necessary to classify the real variants into high confidence class. As a variety of algorithms and dozens of parameters are used in Next Generation Sequencing, different analyses of the same raw data may cause different results (Chapman, O’Rawe et al.). No matter how complex the parameter optimization and machine learning algorithms are, the clinician and/or the patient will want to know the real result.

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