MEDIPIPE: an automated and comprehensive pipeline for cfMeDIP-seq data quality control and analysis

Author:

Zeng Yong1ORCID,Ye Wenbin1,Stutheit-Zhao Eric Y1,Han Ming1,Bratman Scott V12,Pugh Trevor J123ORCID,He Housheng Hansen12

Affiliation:

1. Princess Margaret Cancer Centre, University Health Network , Toronto, Ontario, Canada

2. Department of Medical Biophysics, University of Toronto , Toronto, Ontario, Canada

3. Ontario Institute for Cancer Research , Toronto, Ontario, Canada

Abstract

Abstract Summary Cell-free methylated DNA immunoprecipitation and high-throughput sequencing (cfMeDIP-seq) has emerged as a promising liquid biopsy technology to detect cancers and monitor treatments. While several bioinformatics tools for DNA methylation analysis have been adapted for cfMeDIP-seq data, an end-to-end pipeline and quality control framework specifically for this data type is still lacking. Here, we present the MEDIPIPE, which provides a one-stop solution for cfMeDIP-seq data quality control, methylation quantification, and sample aggregation. The major advantages of MEDIPIPE are: (i) ease of implementation and reproducibility with Snakemake containerized execution environments that will be automatically deployed via Conda; (ii) flexibility to handle different experimental settings with a single configuration file; and (iii) computationally efficiency for large-scale cfMeDIP-seq profiling data analysis and aggregation. Availability and implementation This pipeline is an open-source software under the MIT license and it is freely available at https://github.com/pughlab/MEDIPIPE.

Funder

Cancer Genetics and Epigenetics

Cancer Research Institute Irvington Postdoctoral Fellowship

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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