Stop guessing which statistical test to use. Get guided test selection, assumption checking, and APA-formatted results for your research data. Perfect for students and researchers who need rigorous statistical analysis.

SimPy enables you to model complex systems with processes, queues, and shared resources. Simulate manufacturing lines, service operations, network traffic, and logistics to optimize performance before implementation.

Machine learning models often act as black boxes. SHAP provides a unified framework to explain any model prediction by computing feature contributions using Shapley values from game theory. Use this skill to visualize feature importance, debug model behavior, and implement explainable AI.

Survival analysis handles data where events may not have occurred for all subjects. This skill provides Python tools for time-to-event modeling with censored data using Cox models, Random Survival Forests, SVMs, and specialized evaluation metrics like concordance index.

Process biological sequences, calculate diversity metrics, and perform statistical tests on microbiome and ecological data. This skill provides comprehensive guidance for bioinformatics workflows including sequence alignment, phylogenetic analysis, and ordination.

Single-cell RNA sequencing generates complex datasets requiring specialized analysis. This skill provides a complete workflow for quality control, dimensionality reduction, clustering, and visualization of single-cell gene expression data.

Analyze biological pathways and gene lists using Reactome database. Perform pathway enrichment analysis, map genes to pathways, and explore molecular interactions for systems biology research.

Process proteomics and metabolomics data with comprehensive mass spectrometry tools. This skill provides access to OpenMS algorithms for file format handling, spectral processing, feature detection, and peptide identification workflows.

Multi-objective optimization involves finding trade-off solutions when multiple conflicting objectives must be satisfied. This skill provides comprehensive access to pymoo algorithms including NSGA-II, NSGA-III, and MOEA/D for finding Pareto-optimal solutions and visualizing trade-off fronts.

Build, fit, and validate Bayesian models using PyMC. Create hierarchical models, run MCMC sampling, and compare models with LOO and WAIC metrics.

Healthcare researchers and data scientists struggle with complex clinical data formats and coding systems. PyHealth provides a unified toolkit for loading medical datasets, processing EHR data, training predictive models, and working with standard medical codes.

Process DICOM medical images including CT, MRI, X-ray, and ultrasound. Read, write, anonymize, convert, and extract metadata from healthcare imaging files.

PyDESeq2 enables differential gene expression analysis from bulk RNA-seq count data. Perform statistical testing, multiple comparison correction, and generate publication-ready volcano and MA plots for your genomics research.

Training RL agents requires high-performance parallel environments and efficient algorithms. PufferLib provides optimized PPO+LSTM training with 2-10x speedups through vectorization, shared memory buffers, and multi-agent support.

Process large datasets in memory with Polars, the high-performance DataFrame library. Features lazy evaluation, parallel execution, and Apache Arrow backend for 10x faster operations than pandas.

Data visualization often requires complex code and lacks interactivity for exploration. This skill provides comprehensive guidance for creating interactive, publication-quality charts with Plotly, featuring hover tooltips, zoom, pan, and 40+ chart types for dashboards and data analysis.

Find therapeutic targets and drug candidates using Open Targets Platform data. Access genetic evidence, tractability assessments, safety data, and known drugs for target-disease associations.

This skill provides Python API access to OMERO, a scientific image management platform for microscopy and high-content screening. Connect to OMERO servers, retrieve images, analyze pixel data, and manage annotations programmatically.

This skill provides comprehensive analysis of Neuropixels high-density neural recordings. It handles the complete workflow from raw data loading to publication-ready curated units using SpikeInterface and Kilosort4 algorithms.

Working with graph and network data requires specialized tools for creating structures, computing algorithms, and generating visualizations. This skill provides comprehensive access to NetworkX capabilities for social network analysis, biological pathway mapping, transportation optimization, and relationship modeling.