Method and device for known variation detection based on Bayes testing and Poisson's distribution testing

Abstract

The invention discloses a method and device for known variation detection based on Bayes testing and Poisson's distribution testing. The method comprises the steps that a sequencing and length-reading base sequence, a reference genomic sequence and a sequencing and length-reading sequence reckoned under assumption of existence of a known variance point are provided; comparative detection is conducted on the sequencing and length-reading sequence reckoned under the assumption of existence of the known variance point and the sequencing and length-reading base sequence; and a Bayes testing model and a Poisson's distribution testing model are judged. The method disclosed by the invention has the advantages that SNV or InDel variance can be detected in a high-specificity and high-sensitivity manner.

Description

technical field [0001] The invention relates to the technical field of detection of variation sites of nucleotide sequences, in particular to a known variation detection method and device based on Bayesian and Poisson distribution tests. Background technique [0002] In the field of scientific research and clinical transformation, the detection methods for somatic gene mutations mainly include PCR-Sanger method, PCR-Mass method, ARMS-PCR method and high-throughput capture sequencing method. The samples of these methods are all derived from the lesion tissue samples removed during surgery of cancer patients. The PCR-Sanger sequencing method has low sensitivity, can only detect high-frequency mutations with a mutation rate greater than 20%, and is difficult to detect multi-gene and multi-locus detection; ), the sensitivity is about 5%, and this technology has relatively large limitations; the ARMS-PCR method has good specificity and high sensitivity, and can detect low-freque...

AI Technical Summary

Problems solved by technology

The PCR-Sanger sequencing method has low sensitivity, can only detect high-frequency mutations with a mutation rate greater than 20%, and is difficult to detect multi-gene and multi-locus detection; ), the sensitivity is about 5%, and this technology has relatively large limitations; the ARMS-PCR method has good specificity and high sensitivity, and can detect low-frequency mutations of 1%-5%, but this method can only detect specific known mutations, and Cannot detect multiple genes and multiple loci at the same time

[0003] The data

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