Bioresearch Ld Reference Management
Manage ancestry-specific LD reference panels and perform LD clumping for cross-ancestry MR. Use when the user needs to simulate ancestry-aware LD block structures (AFR/EUR/EAS/SAS/AMR), run greedy distance-based clumping (PLINK --clump style), or compute LD scores for stratified LDSC. Mock mode validates the clumping pipeline; live mode wraps PLINK 2.0 + 1000 Genomes reference panels.
Bioresearch Gwas Harmonization
Harmonize GWAS summary statistics across ancestries for cross-ancestry MR. Use when the user needs to align alleles, flip strands, resolve palindromic SNPs, compute allele-frequency divergence (Fst-like), or identify cross-ancestry genome-wide signal overlap. Supports GWAS-SSF schema; mock mode validates the harmonization pipeline with simulated cross-ancestry GWAS including strand confusion and…
Bioresearch Literature Analysis
Run a reproducible biomedical literature review via the BioResearch Agent literature workflow (PubMed retrieval, entity co-occurrence knowledge graph, structured review outline). Use when the user asks for a literature review, research-gap analysis, or a synthesized reading of PubMed papers on a biomedical topic.
Bioresearch Differential Expression
Perform differential expression (DEG) analysis via the BioResearch Agent biomarker workflow, which computes DEGs (t-test + Bonferroni correction) as its first stage. Use when the user specifically asks for differential expression, DEGs, fold-change, or a volcano plot for a disease or gene-expression dataset.
Bioresearch Ancestry Aware Mr
Run cross-ancestry Mendelian randomization with correlated-pleiotropy modeling (CAUSE-like) and mixture-model pleiotropy detection (MRMix-like), plus per-ancestry IVW, cross-ancestry meta-analysis (FE/RE), and portability assessment. Use when the user needs to test whether a causal effect estimated in one ancestry transfers to others, or to distinguish true causation from correlated horizontal pl…
Bioresearch Biomarker Discovery
Run reproducible biomarker discovery via the BioResearch Agent biomarker workflow (differential expression, pathway enrichment, candidate ranking, volcano plot) over a GEO dataset or synthetic data. Use when the user asks to find gene biomarkers or candidate genes for a disease.
Bioresearch Pathway Enrichment
Run pathway enrichment (hypergeometric KEGG / GO) via the BioResearch Agent biomarker workflow, which performs enrichment after differential expression. Use when the user asks for pathway, GO, or KEGG enrichment analysis for a disease or a gene set.
Bioresearch Introduction
Describe the BioResearch Agent Framework and its capabilities to a user or agent. Use when the user asks "what can BioResearch Agent do", wants an overview of available workflows, or is deciding which skill to invoke for a biomedical research task.
Bioresearch Agent Router
Classify a free-text research intent into the right BioResearch Agent workflow (literature / biomarker / causal / case-study / doctor) using a deterministic, rule-based router. Use when an AI client receives an open-ended biomedical research request and must pick which workflow or skill to invoke — NOT to generate or evaluate hypotheses. No LLM, no network.
Bioresearch Foundation Embeddings
Generate and evaluate single-cell foundation model embeddings (scGPT / UCE / scFoundation). Runs mock-mode pipeline validation by default — simulated embeddings that recover planted cell-type structure. Live mode stubs (pip install scgpt, UCE eval_single_anndata.py, scFoundation get_embedding.py) are documented for real deployment. Use when the user wants to embed scRNA-seq data with foundation m…
Bioresearch Causal Evidence
Run the causal-evidence chain (GWAS → eQTL → colocalization → TWAS → fine-mapping → MR) via the BioResearch Agent causal-evidence workflow. Use when the user wants to test whether a GWAS risk locus acts through a candidate gene's expression, identify the credible set, and check MR consistency. Synthetic loci by default; methodology validation, not a real etiological claim.
Bioresearch Causal Inference
Run two-sample Mendelian randomization via the BioResearch Agent causal workflow (IVW estimation, leave-one-out sensitivity, scatter / funnel plots). Use when the user asks to test a causal effect between an exposure and an outcome (e.g., BMI → Type 2 Diabetes) using genetic instruments.
Bioresearch Disease Case Study
Run a reproducible, real-public-data disease case study that composes the literature → biomarker → causal workflows end-to-end and emits a blind benchmark evaluation (known-gene recovery, pathway sanity, reproducibility hash). Use when the user wants to prove the framework on a real disease (e.g. Parkinson's GSE7621) or asks for a "case study", "validation run", or "benchmark" of the biomedical w…
Bioresearch Environment Check
Verify the BioResearch Agent framework installation, Python/dependency versions, network access to biomedical databases, and output-directory permissions. Use when the user asks to validate the environment, troubleshoot a failed workflow run, or before running any analysis.