DegCre

DegCre generates probabilistic associations between differentially expressed genes (DEGs) and cis-regulatory elements (CREs) by evaluating non-parametric concordance between perturbation-induced differential gene expression and differential regulatory signal at CREs.

Key Features:

• Non-parametric concordance scoring: Evaluates correlations between differential gene expression and differential regulatory signal at CREs without assuming a specific distribution.
• Flexible CRE activity input: Accepts any type of CRE activity measurement including chromatin openness, histone modifications, and transcription factor occupancy.
• Probabilistic association scores: Returns calculated probabilities for CRE-to-gene pair associations.
• Wide distance range assessment: Evaluates CRE-to-gene pairings across a broad range of genomic sequence distances.
• GRanges-based input and output: Accepts DEG TSS and CRE regions as GRanges objects with differential p-values and optional log-fold changes, and returns an annotated Hits object.
• Visualization and format conversion: Provides functionality for visualizing associations and converting results to other formats.

Scientific Applications:

• CRE-to-gene association mapping: Associates cis-regulatory elements with their target genes from perturbation-differential data without requiring chromatin conformation capture techniques.
• Transcriptional regulation analysis: Identifies how differential gene expression in response to perturbations is mediated by changes in transcription factor binding and other regulatory proteins at specific genomic regions.
• Multi-perturbation and multi-omics studies: Applied to diverse datasets using different perturbations with various regulatory signal measurements including chromatin openness, histone modifications, and TF occupancy.
• Validation against orthogonal methods: Performance established by comparison to Hi-C loop calls and CRISPR-validated CRE-to-gene associations.

Methodology:

DegCre uses a nonparametric method to evaluate correlations between measurements of perturbation-induced differential gene expression and differential regulatory signal at CREs to score possible CRE-to-gene associations.