Evidence map›Paper›PMID 31888435›Full record

ArticleBMC bioinformatics2019

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

Shudong Wang, Lihua Wang, Yuanyuan Zhang, Shanchen Pang, Xinzeng Wang

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In one paragraph

Article in BMC bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 citing paper in PubMed.

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5 · Who and what money

Authors and funding

5 authors.

Shudong WangCollege of Computer Science and Technology, China University of Petroleum (East China), Qingdao, Shandong, China.
Lihua WangCollege of Computer Science and Technology, China University of Petroleum (East China), Qingdao, Shandong, China.
Yuanyuan ZhangCollege of Computer Science and Technology, China University of Petroleum (East China), Qingdao, Shandong, China. yyzhang1217@163.com.
Shanchen PangCollege of Computer Science and Technology, China University of Petroleum (East China), Qingdao, Shandong, China.
Xinzeng WangCollege of Mathematics and Systems Science, Shandong University of Science and Technology, Qingdao, Shandong, China. wangelxz@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTumor 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.

resultsConsidering 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.

conclusionsA 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.

Indexed as

AlgorithmsCpG IslandsDNA Copy Number VariationsDNA MethylationEpigenesis, GeneticGene Expression Regulation, NeoplasticHumansNeoplasmsDifferential methylationDNA methylationIntegrating signalTumor purity

Identifiers

PMID31888435
PMCPMC6936156

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