ammawla

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.

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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.

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Generate proper ENCODE citations for publications, grants, and presentations. Use when the user needs to cite ENCODE data, create bibliography entries, write acknowledgment sections, or ensure compliance with ENCODE data use policy.

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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.

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Search and explore ENCODE Project genomics data. Use when the user wants to find experiments, files, or explore what data is available for specific assays, organs, cell lines, or targets.

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Track ENCODE experiments locally with publications, citations, and provenance. Use when the user wants to build a collection of experiments, manage citations, compare experiments, or track data provenance.

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Build comprehensive chromatin accessibility maps by aggregating ATAC-seq and DNase-seq narrowPeak data across multiple ENCODE experiments, donors, and labs. Use when the user wants to answer "where is chromatin accessible in my tissue?" by combining peak calls into a union peak set. Handles cross-lab variation, ATAC vs DNase platform differences, and ENCODE blocklist filtering.

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Guide for multi-experiment batch operations: QC screening, batch download, comparison, and report generation across many ENCODE experiments simultaneously. Use when users need to process 5+ experiments together, create experiment comparison tables, perform batch quality checks, or generate summary reports. Trigger on: batch analysis, multiple experiments, bulk processing, experiment comparison, batch QC, multi-sample, batch download, experiment table, summary report, collection analysis.

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Install bioinformatics tools for ENCODE data analysis. Covers CLI tools (BWA, STAR, samtools, MACS2), R/Bioconductor packages (DESeq2, Seurat, ChIPseeker), Python packages (Scanpy, deeptools), and Nextflow pipeline infrastructure. Generates conda environments, R install scripts, and Python requirements. Use when the user needs to set up a bioinformatics workstation, install tools for a specific assay, create reproducible environments, or troubleshoot dependency issues. Trigger on: install tools, set up environment, conda create, bioinformatics setup, install R packages, install Bioconductor, install pipeline tools.

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Guide for integrating CellxGene Census single-cell data with ENCODE bulk experiments. Use when users need cell-type-specific expression context for ENCODE regulatory data, want to deconvolve bulk ENCODE signals, or validate regulatory elements at single-cell resolution. Trigger on: CellxGene, single-cell atlas, cell type expression, Census, cell type specificity, single-cell context, scRNA-seq atlas.

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Compare ENCODE experiments across different biosamples, tissues, or cell lines to identify tissue-specific regulatory patterns. Use when the user wants cross-tissue comparison, cell-type comparison, tissue-specific elements, differential chromatin, biosample matching, disease vs normal comparison, developmental time course, constitutive vs variable regulation, or multi-tissue data availability mapping. Handles batch effect detection, biosample hierarchy, and comparison design.

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Cross-reference ENCODE data with PubMed, bioRxiv, ClinicalTrials.gov, Open Targets, GTEx, ClinVar, GWAS Catalog, gnomAD, Ensembl, and other scientific databases. Use when the user wants to find publications, preprints, or clinical trials related to ENCODE experiments, chain ENCODE data with other scientific MCP servers, or build translational pipelines from genomic data to clinical application.

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Track exact provenance for every operation on ENCODE data — tool versions, reference files, scripts, parameters, and timestamps — to enable publication-ready methods writing. Use when the user processes ENCODE files, runs any bioinformatics tool, creates filtered/merged datasets, runs pipelines, performs liftover, uses R/Python/Bash for analysis, or needs to document their analysis chain for reproducibility and publication. Also use when the user says "write me methods" to auto-generate methods sections from the provenance log. This skill implements comprehensive provenance documentation: every tool, every version, every reference file, every parameter, every accession — no shortcuts. Use this skill for ANY processing step, ANY file transformation, ANY analysis operation on ENCODE data.

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Use ENCODE functional genomics data for disease mechanism research. Use when the user wants to connect GWAS variants to regulatory elements, annotate disease-associated loci with functional data, identify therapeutic targets from epigenomic data, build disease regulatory models, cross-reference with clinical trials and drug databases, or conduct any disease-focused, pathology-driven, or clinical variant interpretation workflow. Covers the full pipeline from disease-tissue mapping through GWAS variant annotation, heritability enrichment, cancer epigenomics, drug target identification, and clinical trial cross-referencing. Integrates ENCODE with Open Targets, PubMed, ClinicalTrials.gov, and bioRxiv.

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Download ENCODE genomics files (BED, FASTQ, BAM, bigWig, etc.) to the user's machine. Use when the user wants to download data files from ENCODE experiments.

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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), look up gene phenotype associations, or cross-reference ENCODE targets with Ensembl annotations. Also use when the user mentions Ensembl, VEP, variant effect predictor, liftover, assembly conversion, regulatory build, gene lookup, or cross-references between databases.

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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 use when the user mentions GEO, GSE, GSM, GPL, GDS, series matrix, SOFT format, or needs to find expression data in GEO that complements their ENCODE analysis.

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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, wants to filter variants by rarity before functional annotation, or is interpreting ENCODE CRISPR/MPRA results in the context of population genetics. Also use when the user mentions gnomAD, allele frequency, pLI, LOEUF, constraint, rare variants, population frequency, ExAC, or variant filtering.

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Guide for integrating NHGRI-EBI GWAS Catalog associations with ENCODE regulatory data. Use when users need to find GWAS variants in ENCODE peaks, connect regulatory elements to disease associations, or prioritize functional variants using ENCODE annotations. Trigger on: GWAS, genome-wide association, SNP association, trait association, GWAS Catalog, disease association, risk variant, lead SNP, LD proxy.

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Build comprehensive chromatin contact maps by aggregating Hi-C loop calls (BEDPE) across multiple ENCODE experiments, donors, and labs. Use when the user wants to answer "what regions are in 3D contact in my tissue?" by creating a union catalog of chromatin loops. Handles resolution-aware anchor matching, cross-lab variation, and Hi-C-specific quality metrics.

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Build comprehensive histone mark maps by aggregating narrowPeak data across multiple ENCODE experiments, donors, and labs. Use when the user wants to answer "where is this histone mark present in my tissue?" by combining peak calls from multiple studies into a union peak set with confidence annotations. Handles cross-lab batch effects, broad vs narrow marks, and ENCODE blocklist filtering.

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Plan and execute integrative analysis combining multiple ENCODE experiments for cross-dataset or multi-omic workflows. Use when the user wants to combine experiments, perform cross-dataset comparison, multi-omic integration, peak overlap analysis, differential binding, signal correlation, chromatin state segmentation, enhancer-gene linkage, or any analysis that requires merging or comparing data from two or more ENCODE experiments. Covers same-assay cross-sample, multi-omic same-sample, cross-organism, and perturbation integration designs. Guides compatibility checks, batch effect detection, normalization, integration strategy selection, and provenance documentation.

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Build comprehensive DNA methylation maps by aggregating WGBS (Whole Genome Bisulfite Sequencing) data across multiple ENCODE experiments, donors, and labs. Use when the user wants to answer "where is DNA methylated/unmethylated in my tissue?" by combining per-CpG methylation data into tissue-level methylation profiles. Handles coverage filtering, identifies hypomethylated regions (HMRs) and partially methylated domains (PMDs), and manages cross-lab variation.

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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 distance, nearest gene.

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