MEpurity：基于 DNA 甲基化数据估计肿瘤纯度。

MEpurity: estimating tumor purity using DNA methylation data.

机构信息

MOE Key Lab for Intelligent Networks & Networks Security, School of Electronics and Information Engineering, Xi'an Jiaotong University.

The Department of Computer Science and Technology, School of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China.

出版信息

Bioinformatics. 2019 Dec 15;35(24):5298-5300. doi: 10.1093/bioinformatics/btz555.

DOI:10.1093/bioinformatics/btz555

PMID:31297508

Abstract

MOTIVATION

Tumor purity is a fundamental property of each cancer sample and affects downstream investigations. Current tumor purity estimation methods either require matched normal sample or report moderately high tumor purity even on normal samples. It is critical to develop a novel computational approach to estimate tumor purity with sufficient precision based on tumor-only sample.

RESULTS

In this study, we developed MEpurity, a beta mixture model-based algorithm, to estimate the tumor purity based on tumor-only Illumina Infinium 450k methylation microarray data. We applied MEpurity to both The Cancer Genome Atlas (TCGA) cancer data and cancer cell line data, demonstrating that MEpurity reports low tumor purity on normal samples and comparable results on tumor samples with other state-of-art methods.

AVAILABILITY AND IMPLEMENTATION

MEpurity is a C++ program which is available at https://github.com/xjtu-omics/MEpurity.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

摘要

动机

肿瘤纯度是每个癌症样本的基本属性，会影响下游的研究。目前的肿瘤纯度估计方法要么需要匹配的正常样本，要么即使在正常样本上也报告中等偏高的肿瘤纯度。因此，开发一种新的基于计算的方法，能够仅基于肿瘤样本，以足够的精度来估计肿瘤纯度是至关重要的。

结果

在这项研究中，我们开发了 MEpurity，一种基于贝塔混合模型的算法，用于根据肿瘤仅有的 Illumina Infinium 450k 甲基化微阵列数据来估计肿瘤纯度。我们将 MEpurity 应用于癌症基因组图谱（TCGA）癌症数据和癌细胞系数据，结果表明 MEpurity 在正常样本上报告低肿瘤纯度，并且与其他最先进的方法在肿瘤样本上的结果相当。