Advances in next generation sequencing (NGS) enable detection of rare variants at exceptionally low frequencies. Their accurate detection, however, is challenging due in part to errors introduced during sample preparation, target enrichment, and sequencing. The unique molecular identifier (UMI) sequences present in IDT xGen Dual Index UMI Adapters–Tech Access increases calling accuracy of such low-frequency variants. After tagging individual DNA library molecules with these adapters, bioinformatic filters can be applied to identify and correct errors introduced during the sequencing workflow.
In this webinar, Dr. Wendy Lee describes a series of step-by-step analytical workflows developed at IDT for processing data containing UMIs. She highlights methods to extract UMI information, correct errors, and build consensus among multiple observations of an original source molecule. Using a tumor model system employing a mock mixture of normal (NA12878) and tumor (NA24385) cell DNA, Dr. Lee also shows that including UMIs eliminates virtually all false positives, and increases positive predictive value from 69.6% to 98.6%.
Dr. Lee’s presentation demonstrates that consensus analysis increases variant calling accuracy significantly which enables the detection of rare variants at exceptionally low frequencies.
For additional information on xGen Dual Index UMI Adapters–Tech Access, or to place custom orders, please contact our scientific applications support group.