Cobind: quantitative analysis of the genomic overlaps
Tao Ma1, Lingyun Guo2, Huihuang Yan1
1Division of Computational Biology, Mayo Clinic College of Medicine and Science, Rochester, MN 55905, United States.
Bioinformatics Advances
|August 21, 2023
Summary
The cobind package offers novel statistical measures for analyzing genomic interval overlaps, improving accuracy and reproducibility in bioinformatics. This approach enhances the understanding of genomic region interactions and biological insights.
Area of Science:
- Bioinformatics
- Genomics
- Computational Biology
Background:
- Genomic interval overlap analysis is crucial in bioinformatics.
- Current methods rely on arbitrary thresholds, leading to biased results.
- A need exists for quantitative and reproducible overlap assessment.
Purpose of the Study:
- To introduce the cobind package for quantitative assessment of genomic interval collocation.
- To provide robust statistical measures beyond simple overlap counts.
- To improve reproducibility and comparability in genomic analyses.
Main Methods:
- Developed the cobind Python package.
- Incorporated six statistical measures: Jaccard, Sørensen-Dice, Szymkiewicz-Simpson, collocation coefficient, PMI, and normalized PMI.
- Applied methods to ChIP-seq and ATAC-seq data.
Main Results:
- Quantitative assessment of collocation strength between genomic interval sets.
- Effective re-discovery of CTCF cofactors.
- Identification of cancer-specific and oligodendrocyte-specific master regulators.
Conclusions:
- The cobind package provides a powerful tool for analyzing genomic interval overlaps.
- New methods offer improved accuracy and reproducibility in bioinformatics.
- Facilitates deeper understanding of gene regulation and cell development.
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