Neoantigen prediction method and device based on next-generation sequencing and storage medium

Abstract

The invention discloses a neoantigen prediction method and device based on next-generation sequencing and a storage medium. The method comprises the following steps: obtaining genome sequencing data of a tumor sample and a normal sample, and tumor transcriptome sequencing data; carrying out mutation detection on the genome sequencing data to obtain point mutation and insertion and deletion mutation, and carrying out fusion gene mutation detection on the tumor transcriptome sequencing data to obtain fusion gene mutation; detecting the type of an HLA molecule to obtain an HLA molecule type result, matched with the normal sample, of the HLA molecule of the tumor sample; carrying out annotation from gene mutation to amino acid mutation on the point mutation, the insertion and deletion mutationand the fusion gene mutation; predicting peptide fragments subjected to point mutation, insertion and deletion mutation and fusion gene mutation to obtain corresponding mutation prediction peptide fragments; and inputting the mutation prediction peptide fragments and the HLA molecule type result into a neoantigen prediction model, and performing scoring and sorting through the neoantigen prediction model to obtain a neoantigen prediction result. High-quality neoantigen can be accurately obtained from the sequencing data.

Description

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AI Technical Summary

Benefits of technology

This patented technology allows researchers to detect cancerous tissue through mass analysis techniques like MS (mass spectroscopy). It also predicts how likely it will be affected if an antigen matches its target protein. By fitting this algorithm into a computer program trained against patient's DNA sequence data, we are able to make accurate predictions about who may have been infected during future tests without relying solely upon any previous indicators such as histology type or genetic material. Overall, these technical results improve understanding of breast cancer biomarker discovery and development processes.

Problems solved by technology

This patented technical problem addressed in this patents relates to identifying highly pure tumor tissue samples containing certain types of tumour associated genes called tumor Nest Genes (TNGS) through their analysis techniques like SELEX technology. These methods require deep sequencers to analyze sequence data collected during treatment protocols, but they lack consideration regarding how well different sequences interact with each others. Additionally, existing algorithms either use single type of amino acid insertion site(SEQ ID NO.) instead of comprehensive listings of all possible ones, leading to incorrect diagnoses even if some relevant parts are identified correctly.

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