Research & Analysis Workflows

Generates complete FAERS pharmacovigilance study designs for multi-drug or class-level safety comparison inside one predefined SOC or AE family using active comparators, disproportionality analysis, subgroup characterization, and reviewer-facing evidence control.

Design and simulate adaptive clinical trials with interim analyses, decision rules, and operating-characteristic summaries; use when planning adaptive designs or comparing stopping, enrichment, or sample-size re-estimation strategies.

Designs cell-based and animal-based validation plans that translate computational, omics, biomarker, genetic, or clinical findings into experimentally testable validation routes. Always use this skill whenever a user wants to move from an in silico, statistical, or clinical association finding toward wet-lab validation using cell systems, organoid-like systems, xenograft or genetically relevant animal models. It should define the exact claim to test, separate mechanism-testing from association-support and translational-support goals, choose the best-fit model family, specify perturbation strategy, readouts, controls, sequencing of experiments, and four workload configurations (Lite / Standard / Advanced / Publication+) with one recommended primary plan. Never fabricate model availability, reagent availability, species relevance, assay feasibility, phenotype penetrance, expected effect sizes, validation success, or literature references.

Run a submission-readiness preflight on a manuscript before arXiv upload. Use when the user is preparing an arXiv submission, asks to check a paper before uploading, mentions hallucinated or fake references, leftover LLM meta-comments / prompts in text, placeholder data (TODO, TBD, XX%), AI-use disclosure, scholarly integrity, research integrity, or arXiv moderation risk — even if they don't say \"preflight\". Also trigger on phrases like \"check my paper before arXiv\", \"verify my references\", \"scan for AI artifacts\", \"scan for LLM residue\", \"is my submission ready\", or \"review .tex/.bib before submit\".

Use when correcting batch effects in merged bulk expression matrices with sample-level batch metadata while preserving biological group structure and generating before-and-after QC plots. NOT for: single-cell integration, raw FASTQ processing, differential expression without batch labels, or datasets without biological groups.

Generates complete bidirectional multi-phenotype Mendelian randomization research designs from a user-provided exposure family and outcome family.

Bioinformatics literature analysis workflow extraction and customized plan design. Triggered only when the user explicitly refers to a specific paper: the user requests extracting analysis pipelines from a paper, summarizing technical workflows, reproducing analysis approaches...

Use when building a ceRNA regulatory network from a key gene list by combining bundled miRNA-mRNA and miRNA-lncRNA database files, with flat-file CSV exports and PDF visualization in a single output directory. NOT for: differential expression, single-cell analysis, enrichment analysis, or workflows without a key gene list.

Use when estimating relative immune cell infiltration from a bulk expression matrix with a CIBERSORT-style nu-SVR deconvolution workflow based on an LM22 signature matrix, comparing one case group against one control group, and generating structured tables plus immune-fraction plots. NOT for single-cell RNA-seq, spatial data, clinical diagnosis, or workflows that require the original hosted CIBERSORT web service.

Find clinical trials for a gene, variant, or condition from ClinicalTrials.gov + EUCTR, with FHIR R4…

Generates complete comorbidity-oriented shared-biomarker bioinformatics research designs from a user-provided disease pair and validation direction.

Use when identifying stable sample subtypes from bulk expression matrices with ConsensusClusterPlus, including PAC-based model selection and consensus matrix/CDF visualization. NOT for: differential expression analysis, single-cell clustering workflows, or non-expression tables.

Generates complete conventional non-oncology bioinformatics research designs from a user-provided disease context, process-related gene family or biological theme, and…

Generates complete conventional oncology bulk-transcriptome biomarker and hub-gene research designs from a user-provided cancer type and study direction.

Generate tailored AI-focused cover letters using the PSI (Problem-Solution-Impact) methodology. Use when: (1) User wants to create cover letters for AI/ML job applications, (2) User provides a resume and wants LinkedIn job matching, (3) User asks for personalized cover letters based on job postings, (4) User mentions applying for AI Engineer, ML Engineer, or similar technical roles. Integrates market intelligence, LinkedIn research via Playwright, and professional writing standards.

Generates complete cross-disease shared-biomarker bioinformatics research designs from a user-provided disease pair and validation direction.

Use when evaluating the clinical utility of a binary prediction model from a single clinical CSV file by fitting a logistic decision-curve model, plotting decision and clinical-impact curves, and exporting summary outputs. NOT for: survival calibration, ROC-only discrimination analysis, nomogram construction, or time-to-event outcomes.

Use when building a decision tree model in R and generating feature importance ranking outputs. Supports classification and regression, automatic task detection, parameter validation, model evaluation summaries, and exports of feature-importance tables and figures.

Use when screening differentially expressed genes from a bulk expression matrix between two user-specified groups, producing DEG tables, a volcano plot, and a clustered heatmap. Triggers include DEG analysis, volcano plot, clustered heatmap, limma-based two-group comparison, and case-vs-control screening. NOT for single-cell RNA-seq, multi-group contrasts, count-model workflows such as DESeq2/edgeR, or non-expression omics data.

Use when analyzing bulk RNA-seq or microarray expression data to identify differentially expressed genes between two biological groups (case vs control), with volcano plots and heatmap visualization. NOT for: single-cell RNA-seq, methylation analysis, non-expression data.

Generates complete dual-disease shared-transcriptome biomarker and hub-gene research designs from a user-provided disease pair and shared-biology direction.

Use when selecting predictive genes or other molecular features from bulk expression matrices for binary case-vs-control classification with elastic net logistic regression, including coefficient path and cross-validation plots. Trigger keywords: elastic net, glmnet, feature selection, binary classification, lambda.min, lambda.1se. NOT for: survival/Cox modeling, multiclass outcomes, single-cell data, or non-expression tables.

Performs epidemiological analyses including disease modeling (SIR/SEIR), outbreak investigation, risk factor identification, incidence/prevalence estimation, and causal inference from observational data; trigger when users discuss disease spread, public health data, or populat...

Use this skill to compute ESTIMATE immune-related microenvironment scores from a bulk expression matrix, generate an ESTIMATE score heatmap, and optionally generate group-wise ESTIMATE score boxplots plus significance tables when a sample group file is supplied. Trigger keywords: ESTIMATE, immune score, stromal score, tumor microenvironment score. NOT for: immune cell deconvolution, single-cell analysis, differential expression, clinical diagnosis.