The library

open-notebook · Research teams needing self-hosted document analysis with data privacy and multi-speaker podcast generation.

scrna-meta-analysis · Building cell atlases and assessing reproducibility of single-cell findings across studies with detection-aware quality filtering.

search-encode · Discovering existing ENCODE experiments before downloading when exploring what data is available for a tissue/assay.

pacsomatic · Reproducible tumor-normal variant calling when validation and artifact generation must precede execution.

single-cell-encode · Building or validating cell type annotations when authoritative single-cell reference data exists in ENCODE.

paper-lookup · Quick literature discovery and retrieval when you know the title, DOI, or author and need the full paper.

track-experiments · Research projects with many runs where reproducibility and parameter comparison are critical.

ucsc-browser · Inspecting genomic regions when you need authoritative annotation without downloading entire genome builds.

variant-annotation · Clinical variant interpretation when you need comprehensive functional predictions and disease association.

pathml · Computational pathology workflows requiring multiplexed imaging analysis or nucleus segmentation

visualization-workflow · Publishing ENCODE or genomic analysis requiring multi-mark visualization

pathway-enrichment · Interpreting DE genes, CRISPR hits, or cluster markers into biological pathways

pennylane · Hybrid quantum-classical machine learning with automatic differentiation

phylogenetics · Comparative genomics and evolutionary hypothesis testing

polars-bio · Large-scale genomics workflows with fast aggregation and filtering

polars · Data transformations faster and more memory-efficient than pandas

primekg · Discovering drug repurposing via knowledge graph queries

pydeseq2 · RNA-seq differential expression with multi-factor designs

pydicom · Processing medical DICOM images without manual parsing

data-quality-frameworks · Using data-quality-frameworks when it is the specialized tool

pyhealth · Using pyhealth when it is the specialized tool

pymatgen · Using pymatgen when it is the specialized tool

pymc · When you need quantified uncertainty in a statistical model and can validate priors beforehand.

pytorch-lightning · When you want to scale PyTorch training across GPUs without rewriting boilerplate.

dbt-transformation-patterns · When you need reproducible, documented, version-controlled analytics transformations.

scanpy · Specialized task requiring Scanpy expertise

scientific-visualization · Publishing figures in peer-reviewed journals where colorblind accessibility and resolution matter

scikit-bio · Analyzing microbiome or phylogenetic data with built-in ecology metrics and tree operations

scikit-learn · Building classical machine learning pipelines with interpretable algorithms and robust evaluation

scikit-survival · Time-to-event modeling where censored observations are common in observational studies

scvelo · Inferring cell state transitions and RNA velocity from scRNA-seq experiments

scvi-tools · Probabilistic analysis of high-dimensional omics data with learned latent representations

seaborn · Creating statistical plots with minimal code and publication-quality defaults

shap · Debugging model decisions and checking for fairness/bias before production deployment.

simpy · Analyzing queue behavior, capacity planning, and optimizing manufacturing/service systems before implementation.

stable-baselines3 · Quick prototyping of standard RL problems with scikit-learn-like API and proven algorithm implementations.

statistical-analysis · Academic research where test selection, assumption checking, and APA reporting are required.

biomcp · Clinical decision support, drug-disease research, and literature evidence gathering.

statsmodels · Fitting classical statistical models with full diagnostics and academic-grade reporting.

sympy · Educational applications and research requiring exact symbolic manipulation.

tiledbvcf · Storing and querying large-scale genomic cohorts efficiently.

timesfm-forecasting · Zero-shot forecasting without manual feature engineering or hyperparameter tuning.

torch-geometric · When building custom GNN layers for node/link/graph classification.

torchdrug · When building custom architectures for molecular property or protein prediction.

transformers · When loading Hub models for inference or fine-tuning.

unbrowser · When scraping static or client-rendered content without browser overhead.

umap-learn · When visualizing high-dimensional data in lower dimensions.

usfiscaldata · When accessing US government fiscal and budget data.

vaex · Processing billion-row tabular datasets exceeding available RAM with fast aggregations and interactive exploration.

zarr-python · Storing and analyzing multi-dimensional scientific arrays with efficient compression and concurrent access.