cell-type-deconvolution

A fast and accurate deconvolution algorithm based on regularized matrix completion algorithm (ENIGMA)

Fast, deterministic cell-type deconvolution for million-bin spatial transcriptomics

DOT

A Comprehensive Benchmarking of Spatial Deconvolution and Domain Detection Methods across Diverse Tissues and Spatial Transcriptomic Technologies

Code, data and results associated with the "Rare diseases cell-typing" project.

MUSTANG: reference-free MUlti-sample Spatial Transcriptomics data ANalysis with cross-sample transcriptional similarity Guidance

Fast, exact-preserving doublet-mode backend for spacexr RCTD. Up to 15× faster on Xenium, identical calls.

Spatial Deconvolution method with Platform Effect Removal

Deconer: A Comprehensive and Systematic Cell Type Deconvolution Evaluator

cell-free ChIP-seq pipeline

This Github repository holds data, Notebooks and results of running SDePER on both Simulated and Real datasets, and Notebooks for figure panels in manuscript, as well as the codes for running other cell type deconvolution methods.

Fine-tuning MethylBERT to classify single DNA methylation reads into 39 human cell types: a negative result, with leakage audits and all 45 runs.

A Python toolkit for DNA methylation study planning, data preprocessing, QC, and analysis.