公开(公告)号：US20220013193A1

公开(公告)日：2022-01-13

申请号：US17312168

申请日：2019-12-10

Applicant: LIFE TECHNOLOGIES CORPORATION

Inventor： Yong CHU ,  Stephanie SCHNEIDER ,  Rylan SCHAEFFER ,  David WOO

IPC: G16B40/20 ,  G16B30/20 ,  C12Q1/6869 ,  G06N3/08

Abstract: A deep basecaller system for Sanger sequencing and associated methods are provided. The methods use deep machine learning. A Deep Learning Model is used to determine scan labelling probabilities based on an analyzed trace. A Neural Network is trained to learn the optimal mapping function to minimize a Connectionist Temporal Classification (CTC) Loss function. The CTC function is used to calculate loss by matching a target sequence and predicted scan labelling probabilities. A Decoder generates a sequence with the maximum probability. A Basecall position finder using prefix beam search is used to walk through CTC labelling probabilities to find a scan range and then the scan a position of peak labelling probability within the scan range for each called base. Quality Value (QV) is determined using a feature vector calculated from CTC labelling probabilities as an index into a QV look-up table to find a quality score.