数据分析、机器学习、LLM 应用、提示词设计（9112 个）
Perform statistical tests, hypothesis testing, correlation analysis, and multiple testing corrections using scipy and statsmodels. Works with ANY LLM provider (GPT, Gemini, Claude, etc.).
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Clinical Research Bias Assessment - Case-Control Study (NOS) v2.3.0. Use when you need to assess the bias of a case-control study using the Newcastle-Ottawa Scale (NOS) criteria, or when evaluating the quality of a medical paper.
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Use gene structure mapper for data analysis workflows that need structured execution, explicit assumptions, and clear output boundaries.
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Filter compound libraries based on Lipinski's Rule of Five for drug-likeness.
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Generate graphical abstract layout recommendations based on paper abstracts.
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Generate forest plots for meta-analysis of survival data. Input is a CSV file containing study names, HR and 95% confidence intervals, output forest plot PNG and data table CSV. Supports both R and Python scripts.
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Analyzes clinical diagnostic accuracy studies for bias using the QUADAS-2 tool. Use when Claude needs to assess the quality, risk of bias, or applicability of diagnostic accuracy studies (e.g., "Assess this paper using QUADAS-2").
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Machine learning toolkit for genomic interval (BED) data; use it when you need to tokenize BED collections and train embeddings for regions/cells/labels, build consensus peak universes, or run similarity search and downstream ML on chromatin accessibility datasets.
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Use facs gating viz style for data analysis workflows that need structured execution, explicit assumptions, and clear output boundaries.
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Perform comprehensive exploratory data analysis on scientific data files across 200+ file formats. This skill should be used when analyzing any scientific data file to understand its structure, content, quality, and characteristics. Automatically detects file type and generate...
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A Python library for reading, writing, and analyzing geospatial vector data; use it when you need spatial operations (buffer/overlay/join), CRS reprojection, or map visualization on formats like Shapefile/GeoJSON/GeoPackage or PostGIS.
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Generate Circos configuration files for circular genomics data visualization. Supports genomic variations (SNPs, CNVs, structural variants), cell-cell communication networks, and custom track configurations for publication-ready circular plots.
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Generates PI(E)COS structure (Population, Intervention, Comparator, Outcomes, Study Design) from Meta-analysis or study titles. Use when the user wants to extract these elements from a title.
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Use when analyzing FASTQC quality reports from sequencing data, identifying quality issues in NGS datasets, or troubleshooting sequencing problems. Interprets quality metrics and provides actionable recommendations for RNA-seq, DNA-seq, and ChIP-seq data.
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Constraint-based reconstruction and analysis (COBRA) for metabolic models; use when you need to simulate growth/production, analyze flux ranges, or run knockout and medium studies from SBML/JSON/YAML models.
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Draw ROB2 risk-of-bias plots, including a Traffic Light Plot and a Summary Bar Plot. Input is a CSV file with ROB2 assessments for each study; output are two PNG plot files.
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Generate leave-one-out sensitivity analysis plots for meta-analysis. Input is a CSV file containing meta-analysis data; outputs are a sensitivity forest plot (PNG) and a sensitivity data table (CSV) showing pooled effect estimates after excluding each study in turn.
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NGS analysis toolkit. Used for BAM to bigWig conversion, quality control (correlation, PCA, fingerprint plots), heatmaps/feature plots (TSS, peaks), suitable for ChIP-seq, RNA-seq, ATAC-seq visualization.
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Generate meta-analysis forest plots for binary classification data. Input is a CSV file containing study names, event counts and sample sizes for experimental and control groups. Output includes forest plot PNG and data table CSV.
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Digital pathology image processing toolkit for whole slide images (WSI). Supports WSI formats (SVS, TIFF, NDPI), tile-based analysis, and histological image preprocessing workflows.
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Parse Flow Cytometry Standard (FCS) files v2.0–3.1 and extract events/metadata for preprocessing workflows (e.g., when you need NumPy arrays, channel info, or CSV/DataFrame export from cytometry files).
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Generates scientifically sound inclusion and exclusion criteria for Meta-Analysis based on a given title or keywords. Use when user wants to design eligibility criteria for a systematic review or meta-analysis.
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ETE (Environment for Tree Exploration) toolkit for phylogenetic and hierarchical tree analysis; use it when you need to parse/manipulate Newick/NHX trees, detect duplication/speciation events, integrate NCBI taxonomy, and render publication-quality figures.
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Screen full-text papers against inclusion/exclusion criteria, with optional PubMed metadata check using PMID. Use when the user needs to evaluate a paper for a meta-analysis.
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