Best practices for data analysis when using UMI adapters to improve variant detection

Advances in next generation sequencing enable the detection of variants at exceptionally low frequencies. The accurate detection of low-frequency variants is challenging due in part to errors that are introduced during sample preparation, target enrichment, and sequencing. After tagging individual DNA library molecules with adapters containing unique molecular identifiers (UMIs), bioinformatic filters can be applied to identify and correct errors introduced during the sequencing workflow. In this presentation, we walk through the analytical workflows developed at IDT for processing data containing UMIs. We highlight methods to extract UMI information, correct errors, and build consensus among multiple observations of an original source molecule.

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