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.

UNLABELLED: Transcription factor binding events are frequently associated with a pattern of nucleosome occupancy changes in which nucleosomes flanking the binding site increase in occupancy, while those in the vicinity of the binding site itself are displaced. Genome-wide information on enhancer proximal nucleosome occupancy can be readily acquired using ChIP-seq targeting enhancer-related histone modifications such as H3K4me2. Here, we present a software package, BINOCh that allows biologists to use such data to infer the identity of key transcription factors that regulate the response of a cell to a stimulus or determine a program of differentiation. AVAILABILITY: The BINOCh open source Python package is freely available at http://liulab.dfci.harvard.edu/BINOCh under the FreeBSD license.