MuSERA

MuSERA integrates evidence from multiple replicates to detect and quantitatively characterize enriched regions (ERs) across next-generation sequencing (NGS) datasets such as ChIP-seq (transcription factors and histone marks) and DNase-seq.

Key Features:

• Replicate Integration: Combines multiple replicates to increase statistical significance of detected enriched regions (ERs) by aggregating evidence across samples.
• Batch Processing: Supports batch processing of multiple NGS samples and replicates for genome-wide ER analysis.
• Quantitative Evaluations: Performs quantitative assessments of ERs including genomic annotation, nearest ER distance distribution analysis, and global correlation assessment.

Scientific Applications:

• ER discovery in ChIP-seq and DNase-seq: Expands and refines sets of significant ERs in ChIP-seq datasets (transcription factors and histone marks) and in DNase-seq hypersensitive site data.
• Replication-aware ER characterization: Uses replicate-derived evidence to increase detection power and improve characterization of genome-wide ERs.

Methodology:

Combines evidence from multiple replicates to refine genome-wide descriptions of enriched regions (ERs) and performs quantitative analyses such as genomic annotation, nearest ER distance distribution analysis, and global correlation assessment.