Biological information analysis method and device for high-throughput sequencing, equipment and storage medium

Abstract

The invention discloses a biological information analysis method and device for high-throughput sequencing, equipment and a storage medium. The method in one embodiment comprises the following steps of: obtaining high-throughput sequencing data of a to-be-tested gene sequence; analyzing the high-throughput sequencing data to obtain a gene sequence parameter of the to-be-tested gene sequence; extracting a user information parameter corresponding to the to-be-tested gene sequence; and classifying variable features comprising the gene sequence parameter and the user information parameter through a classification model obtained through training so as to obtain a gene classification result of the to-be-tested gene sequence. According to the method, the detection cost is reduced, and false positive and negative results occurring before can be corrected at the same time, so that the detection correctness is improved.

Description

technical field [0001] The present invention relates to the field of biotechnology, in particular to high-throughput sequencing technology, and in particular to a biological information analysis method for high-throughput sequencing, a biological information analysis device for high-throughput sequencing, a computer device, and a computer storage device. medium. Background technique [0002] With the rapid development of genome high-throughput sequencing technology, it has greatly promoted the development of biomedicine, life science and other fields. At present, high-throughput genome sequencing technology has been applied clinically, such as genetic diagnosis of family genetic diseases, non-invasive prenatal testing (NIPT), preimplantation genetic diagnosis and personalized medicine for complex diseases such as tumors, etc. At the same time, more and more researchers are using high-throughput sequencing for scientific research. [0003] At present, the bioinformatics ana...

AI Technical Summary

Problems solved by technology

This method of assessing the risk of non-invasive prenatal screening based on the Z-test value of the comparison sequence data, through technical practice, it is generally found that about 1-10% of the critical values ​​are difficult to judge, and such results are classified into the "gray area" ", needs to be re-tested, which reduces efficiency, increases costs, and has a greater probability of error, resulting in false negatives and false positives

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