Dados e Análise

Guide for using JASPAR transcription factor binding profiles with ENCODE ChIP-seq data. Use when users need to find TF binding motifs in ENCODE peaks, validate ChIP-seq targets with known motifs, or scan regulatory regions for TF binding potential. Trigger on: JASPAR, motif database, binding profile, PWM, position weight matrix, TF motif, motif enrichment, motif scanning, binding site prediction.

Query gnomAD (Genome Aggregation Database) for population allele frequencies, gene constraint scores, and variant annotations to interpret ENCODE regulatory variants. Use when the user needs allele frequencies for variants in ENCODE regulatory elements, wants to assess gene constraint (pLI, LOEUF) for ENCODE target genes, needs population-specific frequencies for GWAS variants overlapping cCREs, w

Guide for integrating GTEx tissue expression data with ENCODE regulatory elements. Use when users need to check if a gene is expressed in a tissue, correlate regulatory elements with expression, or validate ENCODE findings against GTEx. Trigger on: GTEx, tissue expression, gene expression levels, expression atlas, eQTL, tissue-specific expression, TPM values.

Analyze ENCODE functional genomics screens including CRISPR screens, MPRA (Massively Parallel Reporter Assays), and STARR-seq. Find screen data in ENCODE, process results, identify functional elements, and integrate with epigenomic annotations.

Build comprehensive epigenomic profiles for tissues or cell types using ENCODE data. Use when the user wants to characterize chromatin states, assemble histone modification panels, create epigenomic landscapes, run ChromHMM segmentation, identify super-enhancers or bivalent domains, profile regulatory elements across a biosample, or understand epigenetic regulation in a specific biological context

Configure and manage Supabase projects using MCP (Model Context Protocol). Use this skill when working with Supabase databases, setting up MCP servers, designing database schemas, implementing Row Level Security, managing migrations, or building modern data architectures with PostgreSQL. Essential for Supabase development, database design, and AI-powered database operations.

Convert genomic coordinates between assembly versions (GRCh37/hg19 to GRCh38/hg38, mm9 to mm10). Guides UCSC liftOver for BED files, CrossMap for VCF/bigWig, and handles unmapped regions with provenance logging.

Guide for annotating ENCODE peaks with genomic features using ChIPseeker and GREAT. Use when users need to assign peaks to genes, determine genomic feature distribution (promoter, intron, intergenic), or perform gene ontology enrichment of peak-associated genes. Trigger on: peak annotation, ChIPseeker, GREAT, peak to gene, genomic feature, promoter enrichment, gene ontology, peak distribution, TSS

Query the Ensembl REST API for regulatory feature annotations, variant effect prediction (VEP), coordinate liftover, gene lookups, and cross-references. Use when the user needs to annotate variants with VEP (consequence, CADD, REVEL, SpliceAI), check Ensembl Regulatory Build overlap for ENCODE regions, convert coordinates between GRCh37 and GRCh38, resolve gene IDs (Ensembl ↔ symbol ↔ RefSeq), loo

Search, query, and cross-reference NCBI GEO (Gene Expression Omnibus) datasets with ENCODE experiments. Use when the user wants to find GEO accessions for ENCODE experiments, search GEO for complementary datasets, download GEO metadata or series matrices, cross-reference ENCODE and GEO data, find supplementary files from GEO, or link GEO series to ENCODE experiments for provenance tracking. Also u

Conduct rigorous cross-study meta-analysis of scRNA-seq data from ENCODE, integrating multiple single-cell transcriptomic datasets for a tissue/cell type. Use when the user wants to answer "what cell types exist in my tissue and what genes define them?" by combining scRNA-seq data across donors, labs, and platforms. Follows the Mawla et al. 2019 framework for assessing cross-study reproducibility,

Evaluate ENCODE experiment quality using standard metrics and audit flags. Use when the user asks about data quality, wants to filter for high-quality experiments, needs to interpret quality metrics (FRiP, NSC, RSC, NRF, IDR, TSS enrichment, fragment size), wants to understand ENCODE audit warnings, needs to compare quality across experiments, or is deciding whether data is usable for their analys