DLBclass: A Probabilistic Molecular Classifier to Guide Clinical Investigation and Practice in DLBCL.

Diffuse large B-cell lymphoma (DLBCL) is a clinically and molecularly heterogeneous disease. The increasing recognition and targeting of genetically defined DLBCLs highlights the need for robust classification algorithms. We previously characterized recurrent genetic alterations in DLBCL and identified five discrete subtypes, Clusters 1-5 (C1-C5), with unique mechanisms of transformation, immune evasion, candidate treatment targets and different outcomes following standard first-line therapy.

AnnoMate: Exploring and annotating integrated molecular data through custom interactive visualizations.

Manual review is an integral part of any study. As the cost of data generation continues to decrease, the rapid rise in large-scale multi-omic studies calls for a modular, flexible framework to perform what is currently a tedious, error-prone process. We developed , a Python-based package built with Plotly Dash that creates interactive, highly customizable dashboards for reviewing and annotating data.