混合文库测序数据量优化提升肿瘤外科基因检测效能的临床应用与验证OA

Objective To optimize data allocation strategies for tumor libraries of different lengths on the Illumina NextSeq 550 sequencing platform,ensuring detection quality while meeting the timeliness requirements of surgical diagnosis and treatment.Methods In 10 batches of experiments,the output ratio(output data volume/input data volume)of three library types(275 bp/300 bp amplicons,350 bp hybrid capture)was quantified.This quantification was used to determine the cluster generation capability of different libraries.Further analysis was conducted to derive the adjustment range for the data volume ratio of libraries with different lengths.Based on this range,the concentration of each library was adjusted to regulate its final data volume.Results The data volume for 300 bp amplicon libraries should be adjusted to a range of 0.55×to 0.72×.The data volume of 275 bp amplicon libraries should be adjusted in the range of 0.56×to 0.79×.The data volume of 350 bp hybridization capture libraries can be adjusted according to the amount of redundant data on the flow cell to balance data output.Conclusion Adjusting library loading volumes based on output ratios quantifying clustering capabilities across libraries of varying lengths enables balanced output of tumor pooled sequencing data and optimal utilization of chip resources.