Joint analysis of two or more molecular layers on the same samples. Covers method selection, the preprocessing that decides whether integration works at all, MOFA+ factor analysis, similarity network fusion, joint clustering for cancer subtyping, supervised integration, and survival models built on integrated features.
Genomic predictors of radiation response: DNA damage repair pathway profiling, the Radiosensitivity Index and the Genomic-Adjusted Radiation Dose built on it, post-irradiation immune activation signatures, and an honest account of what the abscopal effect can and cannot be predicted from.
Full single-cell RNA-seq pipeline from raw counts to biological interpretation. Covers QC, normalization, batch integration, clustering, annotation, pseudobulk DE, trajectory inference, cell-cell communication, and TF activity. Dual-language: Seurat v5 (R) and scanpy (Python).
Time-to-event analysis for cancer clinical data. Covers Kaplan-Meier, Cox proportional hazards, competing risks, restricted mean survival time, and optimal cutpoint selection using the survival, ggsurvfit, tidycmprsk, and survRM2 packages.
Annotation and clinical interpretation of DNA variants in cancer. Covers VCF normalization and filtering, functional annotation with VEP, germline classification under ACMG/AMP, somatic classification under the AMP/ASCO/CAP tiers and the ClinGen/CGC/VICC oncogenicity standard, tumor mutational burden, microsatellite…