SNITCH: Semi-supervised Non-linear Identification and Trajectory Clustering for High-dimensional Data

SNITCH (Semi-supervised Non-linear Identification and Trajectory Clustering for High-dimensional data) is an R package to analyze ageing-related DNA methylation trajectories. It provides a robust, end-to-end workflow to: Classify CpG sites into linear, non-linear (NL), or non-correlated trajectories. Identify DMPs, VMPs, and non-linear DMPs driven by age. Perform FPCA on smoothed non-linear trajectories to capture complex ageing patterns. Cluster non-linear CpGs with k-means, MFUZZ (fuzzy), or HDBSCAN, and compare results via ARI/AMI. SNITCH aims to be efficient, scalable, and flexible: Try it on your dataset! Please visit the GitHub page for a tutorial on how to use and install SNITCH: https://github.com/fishrscale/SNITCH