scholarly journals Estimating and accounting for tumor purity in the analysis of DNA methylation data from cancer studies

2017 ◽  
Vol 18 (1) ◽  
Author(s):  
Xiaoqi Zheng ◽  
Naiqian Zhang ◽  
Hua-Jun Wu ◽  
Hao Wu
2019 ◽  
Vol 20 (S22) ◽  
Author(s):  
Shudong Wang ◽  
Lihua Wang ◽  
Yuanyuan Zhang ◽  
Shanchen Pang ◽  
Xinzeng Wang

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.


2017 ◽  
Vol 33 (17) ◽  
pp. 2651-2657 ◽  
Author(s):  
Weiwei Zhang ◽  
Hao Feng ◽  
Hao Wu ◽  
Xiaoqi Zheng

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hanyu Zhang ◽  
Ruoyi Cai ◽  
James Dai ◽  
Wei Sun

AbstractWe introduce a new computational method named EMeth to estimate cell type proportions using DNA methylation data. EMeth is a reference-based method that requires cell type-specific DNA methylation data from relevant cell types. EMeth improves on the existing reference-based methods by detecting the CpGs whose DNA methylation are inconsistent with the deconvolution model and reducing their contributions to cell type decomposition. Another novel feature of EMeth is that it allows a cell type with known proportions but unknown reference and estimates its methylation. This is motivated by the case of studying methylation in tumor cells while bulk tumor samples include tumor cells as well as other cell types such as infiltrating immune cells, and tumor cell proportion can be estimated by copy number data. We demonstrate that EMeth delivers more accurate estimates of cell type proportions than several other methods using simulated data and in silico mixtures. Applications in cancer studies show that the proportions of T regulatory cells estimated by DNA methylation have expected associations with mutation load and survival time, while the estimates from gene expression miss such associations.


2010 ◽  
Vol 20 (12) ◽  
pp. 1719-1729 ◽  
Author(s):  
M. D. Robinson ◽  
C. Stirzaker ◽  
A. L. Statham ◽  
M. W. Coolen ◽  
J. Z. Song ◽  
...  

Epigenetics ◽  
2014 ◽  
Vol 9 (3) ◽  
pp. 333-337 ◽  
Author(s):  
Kirsten Hogg ◽  
E Magda Price ◽  
Wendy P Robinson

2021 ◽  
Author(s):  
Sara Gombert ◽  
Kirsten Jahn ◽  
Hansi Pathak ◽  
Alexandra Burkert ◽  
Gunnar Schmidt ◽  
...  

Bisulfite sequencing has long been considered the gold standard for measurement of DNA methylation at single CpG resolution. In the meantime, several new approaches have been developed, which are regarded as less error-prone. Since these errors were shown to be sequence-specific, we aimed to verify the methylation data of a particular region of the TRPA1 promoter obtained from our previous studies. For this purpose, we compared methylation rates obtained via direct bisulfite sequencing and nanopore sequencing. Thus, we were able to confirm our previous findings to a large extent.


2016 ◽  
Vol 32 (16) ◽  
pp. 2517-2519 ◽  
Author(s):  
Alexander J. Titus ◽  
E. Andrés Houseman ◽  
Kevin C. Johnson ◽  
Brock C. Christensen

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