A data set and method for high throughput sequencing somatic mutation detection performance evaluation

Abstract

The invention discloses a data set and method for evaluating the somatic mutation detection performance through high-throughput sequencing. A human reference genome hg19 mutation set, chromosomes, positions and base mutation information of the human reference genome hg19 mutation set are shown in a table 2. The application of the mutation set in evaluating the performance of the somatic mutation detection method comprises the following steps: sampling a BAM file to different sequencing depths, and combining a DNA sample to be detected with a positive control BAM file, so that different proportions of the DNA sample to be detected represent different mutation frequencies; carrying out mutation detection on the mixed data by using software to obtain a detection result, and comparing the detection result with a human reference genome hg19 mutation set; the higher the precision rate, recall rate and F value scores are, the higher the accuracy and authenticity of the method are. According to the method, the mutation true set is used for evaluating the performance of the mutation detection method, the sequencing depth and mutation frequency which are more suitable for being adopted are obtained, and the authenticity and accuracy of mutation detection results are effectively improved.

Description

technical field [0001] The invention belongs to the field of biotechnology, and in particular relates to a data set and a method for performance evaluation of high-throughput sequencing somatic mutation detection. Background technique [0002] Cancer is one of the major diseases threatening human health. Due to the heterogeneity of cancer, the efficacy of the same therapy can vary widely among different individuals with the same cancer type. Therefore, there is currently no single therapy that is universally applicable to all cancers, and more precise therapies are urgently needed to be developed. [0003] In recent years, great progress has been made in the treatment of cancer, especially targeted therapy. Most current targeted therapies are based on the detection of genetic mutations, for example, the tyrosine kinase inhibitors afatinib and erlotinib are used to target the epidermal growth factor receptor (EGFR) in non-small cell lung cancer ( EGFR) mutations; the serin...

AI Technical Summary

Problems solved by technology

However, the current detection performance of somatic mutations based on high-throughput sequencing is not satisfactory. For the same sample, there are large differences in the detection reports given by many commercial organizations. One of the main reasons is the lack of suitable data sets. Evaluation of the Accuracy of Somatic Mutation Detection

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