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Guide for de novo and known motif enrichment analysis of ENCODE ChIP-seq and ATAC-seq peaks using HOMER and MEME Suite. Use when users need to discover TF binding motifs in peaks, validate ChIP-seq targets, or find co-binding partners. Trigger on: motif analysis, HOMER, MEME, de novo motif, motif enrichment, findMotifsGenome, AME, MEME-ChIP, known motif, TF binding motif, co-factor, motif discover

Execute ENCODE DNase-seq pipeline from FASTQ to hotspots and footprints. Child of pipeline-guide. Provides Nextflow execution with Docker and cloud deployment. Use when processing DNase-seq data, calling DNase hypersensitive sites, performing footprinting analysis. Trigger on: DNase-seq pipeline, DNase hypersensitive, DHS, Hotspot2, footprinting, DNase I, chromatin accessibility DNase.

Access ENCODE uniform analysis pipelines, generate user-specific Nextflow/WDL pipelines, manage compute resources, and integrate with cloud platforms. Use when the user wants to understand ENCODE pipelines, run pipelines on their own data, generate custom Nextflow workflows from ENCODE pipeline code, check compute requirements (CPU/GPU/memory), run pipelines in background, or integrate with Google

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 atl

Guide for annotating ENCODE regulatory variants with ClinVar clinical significance. Use when users need to check if variants in ENCODE peaks have clinical associations, find pathogenic variants in regulatory regions, or assess variant clinical impact. Trigger on: ClinVar, clinical significance, pathogenic variant, variant classification, clinical variant, disease variant, VUS, benign, likely patho

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 atl

Converte coordenadas genômicas entre versões de montagem (GRCh37/hg19 para GRCh38/hg38, mm9 para mm10). Orienta o UCSC liftOver para arquivos BED, CrossMap para VCF/bigWig e lida com regiões não mapeadas com registro de proveniência.

Assess the scientific integrity and trustworthiness of publications before relying on their findings. Use this skill whenever evaluating a paper for a workflow, citing a study, building an analysis on published methods, or when a user asks about the reliability of a study. Checks for formal retractions, corrections, expressions of concern, and — critically — informal contradictions where subsequen

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, ba

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.

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 partia

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 map