Tag: epigenomics
CUT/CUT Peak Calling Pipeline
This tool executes a comprehensive Nextflow pipeline for processing CUT or CUT FASTQ data. It handles alignment, spike-in normalization, and generates peak calls using SEACR or MACS2, producing normalized signal tracks and genomic peaks.
ENCODE Multi-Omics Data Integration
Integrates multiple ENCODE data types, including RNA-seq, ATAC-seq, and ChIP-seq, to construct a comprehensive regulatory landscape for specific tissues or cell types. It enables chromatin state annotation, enhancer-gene linkage, and the ch…
Aggregate DNA Methylation Data Across Studies
Construct comprehensive tissue-level DNA methylation landscapes by aggregating WGBS data from multiple ENCODE experiments. The process includes quality-gating, coverage filtering, and the identification of hypomethylated regions and partial…
ENCODE Multi-omic Data Integration
Provides a framework for planning and executing integrative analyses across multiple ENCODE experiments, including multi-omic and cross-sample workflows. It assists with compatibility verification, integration strategy selection, and the re…
Comprehensive Epigenomic Profiling with ENCODE
Assemble comprehensive epigenomic profiles for specific tissues or cell types by systematically gathering histone modifications, chromatin accessibility, and DNA methylation data from ENCODE. It enables the characterisation of chromatin sta…
Functional Genomics for Disease Mechanism Research
This skill facilitates comprehensive disease research by connecting genetic association data (GWAS) with functional genomics data from ENCODE. It annotates disease-associated loci, identifies regulatory elements, and cross-references findin…
Comparing ENCODE data across multiple biosamples
This skill facilitates the systematic comparison of epigenomic data across diverse tissues and cell lines to distinguish constitutive regulatory elements from tissue-specific patterns. It accounts for biosample hierarchy, batch effects, and…
Characterise Regulatory Elements with ENCODE Data
Identify and characterise candidate cis-regulatory elements using ENCODE datasets and the cCRE catalog. The skill enables the discovery of active enhancers, promoter state mapping, and super-enhancer identification using ChromHMM and ROSE.
Integrate multi-omics for regulatory landscape
This skill integrates diverse ENCODE datasets, including RNA-seq, ATAC-seq, and various ChIP-seq assays, to construct a comprehensive regulatory landscape. It allows users to map cell-type-specific regulatory elements by correlating gene ex…
Aggregate DNA Methylation Across ENCODE Studies
Build comprehensive tissue-level DNA methylation landscapes by aggregating WGBS data from multiple ENCODE experiments. The skill handles quality-gating, coverage filtering, and the identification of hypomethylated regions and partially meth…
Comprehensive epigenome profiling using ENCODE data
Assemble a complete epigenomic profile for any tissue or cell type by systematically gathering multiple data modalities, such as histone modifications, accessibility, and methylation, from ENCODE. The resulting profile can then be interpret…
Comparing ENCODE Experiments Across Biosamples
This skill enables the systematic comparison of ENCODE experiments across various tissues, cell lines, and biosamples to identify tissue-specific regulatory patterns. It facilitates the identification of constitutive versus variable regulat…