Mutation analysis method and device for cell-free DNA (cfDNA) sequencing data

Abstract

The invention relates to a mutation analysis method and device for cell-free DNA (cfDNA) sequencing data. The method comprises the following steps: 1, preprocessing original sequencing data; 2, comparing the sequencing data with a reference standard genome, identifying and eliminating PCR repetitive sequences, and correcting comparison errors of sequences to obtain an accurate sequence comparisonfile; 3, identifying tumor-related somatic cell variation sites, adopting a Sentieon software TNScope tool, setting parameters to ensure that cfDNA variation sites higher than 5/10000 variation abundance can be detected, and obtaining a potential tumor-related somatic cell variation site table; and 4, analyzing and identifying the highly credible low-frequency variation, and finally obtaining an expected positive variation analysis result. The method can achieve ultrahigh mutation sensitivity detection and high verification accuracy.

Description

technical field [0001] The present application belongs to the field of bioinformatics, and in particular relates to a mutation analysis method and device for cell-free DNA sequencing data. Background technique [0002] With the rapid development of liquid biopsy technology in the field of precision oncology, a series of related detection technologies and analysis methods with cell-free DNA (cell-free DNA, hereinafter referred to as cfDNA) as the core analyte (analyte) have been formed to assist in the confirmation of tumors. Progress status and related medication guidance. Due to the advantages of non-invasiveness (direct extraction of peripheral blood) and multiple sampling on demand, cfDNA detection and analysis has become an irreplaceable technical solution in oncology research and application. However, there are still many difficulties in identifying low-frequency mutations related to circulating tumor (ctDNA) sources in cell-free DNA by using high-throughput parallel s...

AI Technical Summary

Problems solved by technology

With the application of unique molecule identifiers (UMI) technology in next-generation genome sequencing, the reliability and accuracy of low-frequency (<1%) variant detection in cfDNA has been increased to a certain extent, but there is still no effective protocol to accurately detect this subset of low-frequency mutations

The current reference schemes that can be implemented can be found in references [2,3,4,5,6], where the background noise introduced during the sequencing process (such as references [2,3]) or the plasma cfDNA itself cannot be effectively identified There are many background noises that are not related to tumor development (such as reference [4]), so the above schemes either cannot detect low-frequency mutations (<0.5%), or there are many false positive results in the mutation sites obtained by analysis; and The methods in references [5,6] are unable to exclude the errors introduced in the sequencing technology and the analysis process, so the results of ultra-low frequency mutations will not only miss some mutations, but also introduce some false positive mutations.