bnbc

BNBC corrects and normalizes Hi-C contact maps across multiple samples and replicates to remove unwanted technical batch effects and enable accurate inter-sample comparisons of chromatin interactions.

Key Features:

• Normalization and Batch Correction: Corrects batch effects and normalizes Hi-C data across samples and replicates to enable reliable comparison of contact maps.
• Handling Unwanted Variation: Identifies and mitigates unwanted technical variation that can vary across the Hi-C contact map and confound analyses.
• Improved Comparisons Across Samples: Enables improved inter-sample comparisons for analyses such as quantitative trait loci (QTL) mapping and differential enrichment studies across cell types.

Scientific Applications:

• Quantitative Trait Loci (QTL) Analysis: Facilitates identification of genetic loci in QTL mapping by providing normalized Hi-C contact maps across samples.
• Differential Enrichment Studies: Supports differential enrichment comparisons of chromatin interactions across cell types by reducing technical artifacts.

Methodology:

Detects and corrects batch effects in Hi-C data by identifying and mitigating technical variation that changes across contact maps.