zamushwani

30 mods across 1 repository, 1 stars between them.

zamushwani/biomedical-ai-skills

Skill Claude CodeCodex

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.

1 2d ago A 0 tokens original MIT

zamushwani/biomedical-ai-skills

Skill Claude CodeCodex

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.

1 2d ago A 0 tokens original MIT

single-cell-atlas

27

zamushwani/biomedical-ai-skills

Skill Claude CodeCodex

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).

1 2d ago A 0 tokens original MIT

zamushwani/biomedical-ai-skills

Skill Claude CodeCodex

Processing and analysis of spatially resolved transcriptomics across sequencing-based (Visium, Visium HD, Slide-seq, Stereo-seq) and imaging-based (Xenium, MERSCOPE, CosMx) platforms. Covers loading, QC, normalization, and spatially variable gene detection. Dual-language: Python (squidpy/SpatialData) and R…

1 2d ago A 0 tokens original MIT

survival-analysis

29

zamushwani/biomedical-ai-skills

Skill Claude CodeCodex

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.

1 2d ago A 0 tokens original MIT

variant-annotation

30

zamushwani/biomedical-ai-skills

Skill Claude CodeCodex

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…

1 2d ago A 0 tokens original MIT