PEIS: A novel approach of tumor purity estimation by identifying information sites through integrating signal based on DNA methylation data

Abstract

Background: Tumor purity plays an important role in understanding the pathogenic mechanism of tumors. The purity of tumor samples is highly sensitive to tumor heterogeneity. Due to Intratumoral heterogeneity of genetic and epigenetic data, it is suitable to study the purity of tumors. Among them, there are many purity estimation methods based on copy number variation, gene expression and other data, while few use DNA methylation data and often based on selected information sites. Consequently, how to choose methylation sites as information sites has an important influence on the purity estimation results. At present, the selection of information sites was often based on the differentially methylated sites that only consider the mean signal, without considering other possible signals and the strong correlation among adjacent sites. Results: Considering integrating multi-signals and strong correlation among adjacent sites, we propose an approach, PEIS, to estimate the purity of tumor samples by selecting informative differential methylation sites. Application to 12 publicly available tumor datasets, it is shown that PEIS provides accurate results in the estimation of tumor purity which has a high consistency with other existing methods. Also, through comparing the results of different information sites selection methods in the evaluation of tumor purity, it shows the PEIS is superior to other methods. Conclusions: A new method to estimate the purity of tumor samples is proposed. This approach integrates multi-signals of the CpG sites and the correlation between the sites. Experimental analysis shows that this method is in good agreement with other existing methods for estimating tumor purity.