Sequencing-based DNA methylome deconvolution pipelines

Introduction

Analysis of cell-type heterogeneity based on cell mixture (bulk) omic profiles is an active area of research, known as cell-type deconvolution. Sequencing-based DNA methylation data such as whole genome bisulfite sequencing (WGBS), in particular, has high capacity for cell-type deconvolution through leveraging read-level information. We thoroughly evaluated five previously published decovolution methods for sequencing data: Bayesian epiallele detection (BED), PRISM, csmFinder + coMethy, ClubCpG, DXM and MethylPurify, together with two array-based methods, MeDeCom and Houseman, as a comparison group. This github page describes the pipeline of each method including all the details (e.g. input data format, how to analyse the output results).

Our evaluation results

This work is published in Briefings in Bioinformatics Please find the results and our paper here https://doi.org/10.1093/bib/bbac248

References

• BED: James E Barrett, Andrew Feber, Javier Herrero, Miljana Tanic, Gareth A Wilson, Charles Swanton, and Stephan Beck. Quantification of tumour evolution and heterogeneity via bayesian epiallele detection. BMC bioinformatics, 18(1):1–10, 2017.

• ClubCpG: C Anthony Scott, Jack D Duryea, Harry MacKay, Maria S Baker, Eleonora Laritsky, Chathura J Gunasekara, Cristian Coarfa, and Robert A Waterland. Identification of cell type-specific methylation signals in bulk whole genome bisulfite sequencing data. Genome biology, 21(1):1–23, 2020.

• csmFinder+coMethy: Liduo Yin, Yanting Luo, Xiguang Xu, Shiyu Wen, Xiaowei Wu, Xuemei Lu, and Hehuang Xie. Virtual methylome dissection facilitated by single-cell analyses. Epigenetics & chromatin, 12(1):1–13, 2019.

• DXM: Fong, Jerry, et al. "Determining subpopulation methylation profiles from bisulfite sequencing data of heterogeneous samples using DXM." Nucleic acids research 49.16 (2021): e93-e93.

• MethylPurify: Xiaoqi Zheng, Qian Zhao, Hua-Jun Wu, Wei Li, Haiyun Wang, Clifford A Meyer, Qian Alvin Qin, Han Xu, Chongzhi Zang, Peng Jiang, et al. Methylpurify: tumor purity deconvolution and differential methylation detection from single tumor dna methylomes. Genome biology, 15(7):1–13, 2014.

• PRISM: Dohoon Lee, Sangseon Lee, and Sun Kim. Prism: methylation pattern-based, reference-free inference of subclonal makeup. Bioinformatics, 35(14):i520–i529, 2019.

• Houseman's method: Eugene Andres Houseman, William P Accomando, Devin C Koestler, Brock C Christensen, Carmen J Marsit, Heather H Nelson, John K Wiencke, and Karl T Kelsey. Dna methylation arrays as surrogate measures of cell mixture distribution. BMC bioinformatics, 13(1):86, 2012.

• MeDeCom: Pavlo Lutsik, Martin Slawski, Gilles Gasparoni, Nikita Vedeneev, Matthias Hein, and Jörn Walter. Medecom: discovery and quantification of latent components of heterogeneous methylomes. Genome biology, 18(1):1–20, 2017.