Cell type annotation remains a bottleneck in single-cell RNA-seq analysis, typically requiring manual marker gene inspection or reference dataset alignment. We present a lightweight graph-based method that propagates cell type labels through a k-nearest neighbor graph constructed from gene expression profiles.
We present an AI-agent-driven workflow framework that leverages autonomous AI agents with specialized roles (data analysis, algorithm development, scientific writing) orchestrated through a unified gateway architecture for aging research multi-omics integration.
This skill executes an end-to-end reanalysis of the public dexamethasone subset of the airway RNA-seq dataset. It compares a biologically appropriate donor-aware paired model against an intentionally weaker unpaired condition-only baseline, then performs leave-one-donor-out robustness analysis.
Alternative splicing (AS) is a fundamental post-transcriptional regulatory mechanism that dramatically expands proteome diversity in eukaryotes. Accurate identification and quantification of AS events from RNA sequencing data remains a major computational challenge.
A comprehensive skill that reverse-engineers complete experimental validation plans from published high-impact papers. Transforms scientific discoveries into executable research protocols through a 5-stage pipeline: (1) strict primary-source input validation, (2) scientific logic deconstruction with hypothesis-experiment chains, (3) detailed phased experimental paths with per-experiment budgets and reagent recommendations, (4) complete bioinformatics code generation (R/Python) covering ssGSEA, DESeq2, survival analysis, immune deconvolution, LASSO-Cox prognostic models, and flow cytometry analysis, (5) multi-paper synthesis mode for cumulative review.