Genomics

This skill provides comprehensive documentation for integrating with DNAnexus, a cloud platform for biomedical data analysis and genomics. It covers app/applet development, file upload/download operations, job execution, workflow orchestration, and the dxpy Python SDK for building genomics pipelines with FASTQ, BAM, and VCF files.

This skill enables querying the Reactome database for biological pathway analysis. It supports pathway enrichment analysis on gene/protein lists, expression data analysis, gene-to-pathway mapping, and visualization of results in the Reactome Pathway Browser for systems biology research.

This skill enables querying the KEGG (Kyoto Encyclopedia of Genes and Genomes) bioinformatics database through REST API calls. It supports pathway analysis, gene-pathway mapping, metabolic pathway exploration, drug interaction checking, and ID conversion between KEGG and external databases like UniProt and PubChem.

This skill provides guidance for querying the NHGRI-EBI GWAS Catalog, a comprehensive database of genome-wide association studies. It includes documentation on searching for SNP-trait associations, retrieving study metadata, accessing summary statistics, and integrating with Python for genetic epidemiology research and polygenic risk score development.

This skill enables access to the NCBI Gene Expression Omnibus (GEO), a public repository containing over 264,000 gene expression studies. It provides tools to search for datasets, download microarray and RNA-seq data, parse SOFT/matrix files, and perform expression analysis including differential expression and meta-analysis across studies.

This skill enables querying the Ensembl genome database, a comprehensive resource for vertebrate genomic data maintained by EMBL-EBI. It supports gene information retrieval, DNA/protein sequence fetching, variant effect prediction using VEP, ortholog discovery, and coordinate mapping between genome assemblies for over 250 species.

This skill provides comprehensive guidance for accessing the European Nucleotide Archive (ENA), a public repository for nucleotide sequence data. It documents REST APIs for searching samples, studies, and assemblies, retrieving FASTQ files and genome sequences, querying taxonomic information, and bulk downloading datasets via FTP or Aspera for genomics research pipelines.

This skill provides programmatic access to COSMIC (Catalogue of Somatic Mutations in Cancer), the world's largest cancer mutation database. It allows downloading mutation data, Cancer Gene Census lists, mutational signatures, gene fusions, and drug resistance information for cancer research and bioinformatics workflows.

A comprehensive guide for accessing NCBI's ClinVar database to query clinical significance of human genetic variants. Provides documentation on searching variants by gene/position, interpreting pathogenicity classifications (ACMG/AMP guidelines), downloading bulk data via FTP, and annotating VCF files with clinical significance.

A comprehensive documentation skill for scvi-tools, a Python framework for probabilistic deep generative models in single-cell genomics. It provides guidance on models for RNA-seq, ATAC-seq, multimodal data integration, spatial transcriptomics, and specialized modalities like methylation and cytometry analysis.

Pysam is a documentation skill for genomic data analysis using Python. It provides comprehensive reference guides for reading and writing sequencing alignment files (SAM/BAM/CRAM), genetic variant files (VCF/BCF), and sequence files (FASTA/FASTQ), along with practical code examples for bioinformatics workflows like coverage analysis and variant filtering.

gget is a bioinformatics tool that provides quick access to over 20 genomic databases through both command-line and Python interfaces. It enables gene searches, BLAST/BLAT sequence analysis, AlphaFold structure predictions, single-cell expression queries, enrichment analysis, and disease/drug associations - all through a unified, consistent interface.

deepTools is a bioinformatics skill for analyzing next-generation sequencing (NGS) data. It helps with quality control, normalization, and visualization of ChIP-seq, RNA-seq, and ATAC-seq experiments, providing workflow generators and comprehensive documentation for common analyses.

This skill provides comprehensive guidance for programmatically accessing the CZ CELLxGENE Census, a collection of 61+ million single-cell genomics data. It covers querying expression data by cell type, tissue, or disease, integrating with PyTorch for machine learning, and using scanpy for analysis workflows.

This skill provides comprehensive documentation and reference material for working with AnnData, a Python package for handling annotated data matrices used in single-cell genomics. It covers creating, reading, writing, and manipulating AnnData objects, along with best practices for memory management and integration with the scverse ecosystem (Scanpy, Muon, PyTorch).

High-performance toolkit for genomic interval analysis in Rust with Python bindings. Use when working with genomic regions, BED files, coverage tracks, overlap detection, tokenization for ML models, or fragment analysis in computational genomics and machine learning applications.

This skill should be used when working with genomic interval data (BED files) for machine learning tasks. Use for training region embeddings (Region2Vec, BEDspace), single-cell ATAC-seq analysis (scEmbed), building consensus peaks (universes), or any ML-based analysis of genomic regions. Applies to BED file collections, scATAC-seq data, chromatin accessibility datasets, and region-based genomic feature learning.

Autonomous biomedical AI agent framework for executing complex research tasks across genomics, drug discovery, molecular biology, and clinical analysis. Use this skill when conducting multi-step biomedical research including CRISPR screening design, single-cell RNA-seq analysis, ADMET prediction, GWAS interpretation, rare disease diagnosis, or lab protocol optimization. Leverages LLM reasoning with code execution and integrated biomedical databases.