Cancer is a poligenetic disease with each cancer type having a different mutation profile. Genomic data can be utilized to detect these profiles and to diagnose and differentiate cancer types. Variant calling provide mutation information. Gene expression data reveal the altered cell behaviour. The combination of the mutation and expression information can lead to accurate discrimination of different cancer types. In this study, we utilized and transferred the information of existing mutations for a novel gene selection method for gene expression data. We tested the proposed method in order to diagnose and differentiate cancer types. It is a disease specific method as both the mutations and expressions are filtered according to the selected cancer types. Our experiment results show that the proposed gene selection method leads to similar or improved performance metrics compared to classical feature selection methods and curated gene sets.

中文翻译：

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一种用于癌症类型分类任务的基因表达数据的新基因选择方法

癌症是一种多发性疾病，每种癌症类型都有不同的突变谱。基因组数据可用于检测这些特征并诊断和区分癌症类型。变异调用提供变异信息。基因表达数据揭示了细胞行为的改变。突变和表达信息的结合可以导致对不同癌症类型的准确区分。在这项研究中，我们利用并转移了现有突变的信息，为基因表达数据提供了一种新的基因选择方法。我们测试了所提出的方法以诊断和区分癌症类型。这是一种疾病特定的方法，因为突变和表达都根据选定的癌症类型进行过滤。