Open-source web tools for molecular pathology, clinical genomics, and diagnostic decision support.
Submit mutations and copy-number alterations to rank probable tumor types using AACR GENIE prevalence priors. Posterior likelihoods guide differential diagnosis for cancers of unknown primary.
Upload a MAF file to classify endometrial carcinomas into POLEmut, MMRd, p53abn, or NSMP. Integrates sequencing data with optional IHC results per WHO 2020 criteria and Swedish national guidelines.
Visualize and compare next-generation sequencing results across two timepoints — for instance baseline vs. relapse — to track clonal evolution and emerging resistance mutations.
Classify PI3K pathway alterations in colorectal cancer to determine eligibility for adjuvant aspirin therapy per the ALASCCA trial (Martling et al., NEJM 2025). Covers Group A (PIK3CA hotspots) and Group B (PIK3CA, PIK3R1, PTEN) alterations.
Python reimplementation of the MSK vcf2maf tool. Converts VEP- or SnpEff-annotated VCFs to MAF v2.4 format with effect prioritization, multi-allelic splitting, and broad caller support. No Perl or C dependencies — install via pip.
Single-sample tissue-of-origin inference using an AutoGluon ensemble trained on AACR GENIE v18 data. Classifies 22 tumor types from mutations, copy-number, structural variants, and clinical features with 85% balanced accuracy.