Complex disease state evaluation method based on high-throughput sequencing data and clinical phenotype construction and application

Abstract

The invention relates to the field of gene detection and bioinformatics, and discloses a method for mining complex disease markers based on transcriptome data, exon group / genome data and clinical phenotypes. The invention designs a set of calculation method for constructing a complex disease state evaluation model by integrating high-throughput sequencing data and clinical phenotypes, the calculation method is applied to targeted medication of colorectal cancer, pancreatic ductal cancer and pancreas ductal cancer, biomarkers related to diseases are screened respectively, and the correspondingdisease state evaluation model is formed. The marker considering both accuracy and mechanism interpretability is constructed through the method and can be used for prognosis evaluation of complex diseases, treatment effect prediction, treatment scheme assistant decision making and the like.

Description

technical field [0001] The present invention relates to the technical fields of gene detection and bioinformatics, in particular to a complex disease state assessment method based on high-throughput sequencing data and clinical phenotypes, and related detection panel design and implementation cases. Background technique [0002] The first-generation sequencing technology obtains the base information at a specific position of the sequence through the dideoxy terminal termination method or chemical cleavage method, and reads the nucleic acid sequence by electrophoresis and development. Gene chip technology, by hybridizing with a set of nucleic acid probes of known sequences for nucleic acid sequence determination, has achieved high-throughput parallelization. The disadvantages are that the repeatability and sensitivity need to be enhanced, and the analysis range is not wide enough. Next-generation sequencing technology, also known as next-generation sequencing technology (...

AI Technical Summary

Problems solved by technology

Gene chip technology, by hybridizing with a set of nucleic acid probes of known sequence for nucleic acid sequence determination, realizes high-throughput parallelization, but the disadvantages are that the repeatability and sensitivity need to be enhanced, and the analysis range is not wide enough

Next-generation sequencing technology, also known as next-generation sequencing technology (next-generation sequencing, NGS), is different from the first-generation sequencing technology. It achieves high-throughput parallel sequencing through in vitro fragment amplification and sequencing while synthesizing. The main disadvantages are read length

2) Detection and evaluation content is relatively single, with limited functions

At present, due to gene collection and screening capabilities and sequencing costs, the same marker detection scheme covers relatively few genes. In practical applications, single site or small fragment mutations are used as the main evaluation index. In recent years, gene expression levels and detection of all genes in the panel The overall mutation level as a marker evaluation scheme has attracted increasing attention; in terms of function, it mainly predicts the effect of site- or gene-related targeted drugs, and has limited guiding significance for a wider range of surgery, chemotherapy, radiotherapy, and immunotherapy

3) Marker design and supporting data analysis tools do not make full use of multivariate information

At present, most of the design schemes only focus on drug guidelines, labels and limited literature collection. The technical route focuses on a single omics level, and there are few comprehensive analyzes based on large-scale sequencing results, public databases and text mining technologies. It covers a variety of molecular omics and Multivariate data integration analysis of clinical phenotype information is seriously insufficient

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