3. Data, Science & AI

Database and analysis toolkit for cell type annotation, ligand-receptor analysis, and cell-cell communication network visualization in single-cell data.

Enables connection to user's own database or CSV file to replace demo data, supporting data source configuration and switching.

Generates realistic UK-focused fake data for recruitment systems including clients, candidates, jobs, and placements with customizable record counts and industry sectors.

Expert guidance on statistical analysis, regression methods, Monte Carlo simulations, and hypothesis testing for fantasy football player performance modeling.

Validates FTD analysis output files for JSONL format, field completeness, score validity, and TALD scale structural requirements.

Provides AI-powered image analysis including text extraction, description, summary, and content explanation from user-uploaded images.

Generates dbt test suites compliant with FF Analytics data quality standards, covering grain uniqueness, FK relationships, and freshness checks for data transformation models.

Performs single-cell RNA-seq data analysis using Scanpy on .h5ad files within a conda environment.

Comprehensive toolkit for spatial transcriptomics data analysis featuring core APIs, tutorials, and data processing functions.

Provides deep learning tools for single-cell chromatin accessibility data analysis, including scATAC-seq processing and integration with scRNA-seq.

Automates LLM model and provider selection, optimizing cost, ensuring fallbacks, and enabling multi-model strategies.

Provides API and documentation for spatial transcriptomics analysis, enabling researchers to process and visualize spatial gene expression data.

Builds and manages collaborative AI agent teams (crews) for task automation, workflow orchestration, and enterprise AI solutions.

Generates dbt models following FF Analytics Kimball and 2x2 stat patterns with proper grain, tests, and Parquet configuration for data warehousing.

Automates structured carbon report creation by processing Carbon ACX dataset data and applying customizable templates for monthly, quarterly, compliance, and executive formats.

Comprehensive toolkit for integrating and analyzing single-cell multi-omics data with full API documentation, tutorials, and graph-based analysis capabilities.

Complete Python toolkit for cell-cell interaction analysis with full documentation, 60 core files, and 72 visualizations.

Spatial transcriptomics analysis tool featuring precise file name-based categorization and comprehensive documentation for biological data processing.

Converts Heart Atlas Jupyter notebooks to HTML for local documentation and sharing without requiring a notebook environment.

Comprehensive toolkit for RNA velocity analysis in single-cell transcriptomics, including full API documentation, tutorials, dynamic modeling, and visualization tools.

Comprehensive toolkit for single-cell trajectory inference with full documentation, tutorials, and API for RNA-seq data analysis.

Comprehensive spatial transcriptomics analysis tool with documentation, notebooks, and source code for biological data processing.

Python toolkit for spatial transcriptomics analysis with comprehensive documentation and tutorials.

Provides tools for analyzing, visualizing, and managing spatial multi-modal and multi-scale data, particularly in spatial omics using the SpatialData Python ecosystem.