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: For practical and robust de novo identification of genomic fusions and breakpoints from targeted paired-end DNA sequencing data, we developed Fusion And Chromosomal Translocation Enumeration and Recovery Algorithm (FACTERA). Our method has minimal external dependencies, works directly on a preexisting Binary Alignment/Map file and produces easily interpretable output. We demonstrate FACTERA's ability to rapidly identify breakpoint-resolution fusion events with high sensitivity and specificity in patients with non-small cell lung cancer, including novel rearrangements. We anticipate that FACTERA will be broadly applicable to the discovery and analysis of clinically relevant fusions from both targeted and genome-wide sequencing datasets. AVAILABILITY AND IMPLEMENTATION: http://factera.stanford.edu.