SUMMARY: DNA methylation (DNAm) of neighbouring CpG sites is highly correlated, making DNAm function in terms of blocks. DNAm patterns and functionality are linked to both chromatin structure of DNA and gene regulation. Defining biologically meaningful DNA methylation blocks from whole-genome bisulfite sequencing (WGBS) data remains challenging, as most existing methods rely on fixed genomic windows rather than the observed methylation pattern. We present FUSE, a data-driven segmentation method that captures intrinsic methylation segments directly from WGBS data by jointly analyzing multiple samples. FUSE identifies spatially homogeneous methylation blocks shared across the input cohort while allowing different methylation states across samples. Applied to 61 WGBS samples from the ENCODE database, FUSE identified segments which overlap significantly with promoters, enhancers, and repetitive elements. FUSE was able to recover the true segment breakpoints in synthetic data with high sensitivity under increased levels of noise. As such, FUSE facilitates post hoc methylation analyses by aggregating coherent CpG sites into candidate segments for downstream differential methylation testing or other comparative studies. AVAILABILITY AND IMPLEMENTATION: FUSE is implemented as an R-package methFuse, available at https://github.com/holmsusa/methFuse and https://cran.r-project.org/package=methFuse. A GenomeSpy visualization of the data is available at https://csbi.ltdk.helsinki.fi/p/fuse_encode_gs/.

SUMMARY: Spatial and temporal intra-tumor heterogeneity drives tumor evolution and therapy resistance. Existing visualization tools often fail to capture both dimensions simultaneously. To address this, we developed Jellyfish, a tool that integrates phylogenetic and sample trees into a single plot, providing a holistic view of tumor evolution and capturing both spatial and temporal evolution. Available as a JavaScript library and R package, Jellyfish generates interactive visualizations from tumor phylogeny and clonal composition data. We demonstrate its ability to visualize complex subclonal dynamics using data from ovarian high-grade serous carcinoma. AVAILABILITY AND IMPLEMENTATION: Jellyfish is freely available with MIT license at https://github.com/HautaniemiLab/jellyfish (JavaScript library) and https://github.com/HautaniemiLab/jellyfisher (R package).

SUMMARY: Anduril is an analysis and integration framework that facilitates the design, use, parallelization and reproducibility of bioinformatics workflows. Anduril has been upgraded to use Scala for pipeline construction, which simplifies software maintenance, and facilitates design of complex pipelines. Additionally, Anduril's bioinformatics repository has been expanded with multiple components, and tutorial pipelines, for next-generation sequencing data analysis. AVAILABILITYAND IMPLEMENTATION: Freely available at http://anduril.org. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.