IGN: Invariable gene set-based normalization for chromatin accessibility profile data analysis
Chromatin accessibility profiles generated using ATAC-seq or DNase-seq carry functional information of the regulatory genome that controls gene expression. Appropriate normalization of ATAC-seq and DNase-seq data is essential for accurate differential analysis when studying chromatin dynamics. Exist...
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| Language: | English |
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Elsevier
2025-01-01
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| Series: | Computational and Structural Biotechnology Journal |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2001037025000170 |
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| author | Shengen Shawn Hu Hai-Hui Xue Chongzhi Zang |
| author_facet | Shengen Shawn Hu Hai-Hui Xue Chongzhi Zang |
| author_sort | Shengen Shawn Hu |
| collection | DOAJ |
| description | Chromatin accessibility profiles generated using ATAC-seq or DNase-seq carry functional information of the regulatory genome that controls gene expression. Appropriate normalization of ATAC-seq and DNase-seq data is essential for accurate differential analysis when studying chromatin dynamics. Existing normalization methods usually assume the same distribution of genomic signals across samples; however, this assumption may not be appropriate when there are global changes in chromatin accessibility levels between experimental conditions/samples. We present IGN (Invariable Gene Normalization), a method for ATAC-seq and DNase-seq data normalization. IGN normalizes the promoter chromatin accessibility signals for a set of genes that are unchanged in expression, usually obtained from accompanying RNA-seq data, and extrapolating to normalize the genome-wide chromatin accessibility profile. We demonstrate the effectiveness of IGN in analyzing central memory CD8+ T cell activation, a system with anticipated global reprogramming of chromatin and gene expression, and show that IGN outperforms existing methods. As the first chromatin accessibility normalization method that accounts for global differences, IGN can be widely applied to differential ATAC-seq and DNase-seq analysis. The package and source code are available on GitHub at https://github.com/zang-lab/IGN. |
| format | Article |
| id | doaj-art-3b398231309743fc823aa516256269f6 |
| institution | Kabale University |
| issn | 2001-0370 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Computational and Structural Biotechnology Journal |
| spelling | doaj-art-3b398231309743fc823aa516256269f62025-01-29T05:00:31ZengElsevierComputational and Structural Biotechnology Journal2001-03702025-01-0127501507IGN: Invariable gene set-based normalization for chromatin accessibility profile data analysisShengen Shawn Hu0Hai-Hui Xue1Chongzhi Zang2Department of Genome Sciences, University of Virginia, Charlottesville, VA 22908, USA; UVA Comprehensive Cancer Center, University of Virginia, Charlottesville, VA 22908, USA; Correspondence to: Department of Genome Sciences, University of Virginia, PO Box 800717, Charlottesville, VA 22908, USA.Center for Discovery and Innovation, Hackensack University Medical Center, Nutley, NJ 07110, USADepartment of Genome Sciences, University of Virginia, Charlottesville, VA 22908, USA; UVA Comprehensive Cancer Center, University of Virginia, Charlottesville, VA 22908, USA; Correspondence to: Department of Genome Sciences, University of Virginia, PO Box 800717, Charlottesville, VA 22908, USA.Chromatin accessibility profiles generated using ATAC-seq or DNase-seq carry functional information of the regulatory genome that controls gene expression. Appropriate normalization of ATAC-seq and DNase-seq data is essential for accurate differential analysis when studying chromatin dynamics. Existing normalization methods usually assume the same distribution of genomic signals across samples; however, this assumption may not be appropriate when there are global changes in chromatin accessibility levels between experimental conditions/samples. We present IGN (Invariable Gene Normalization), a method for ATAC-seq and DNase-seq data normalization. IGN normalizes the promoter chromatin accessibility signals for a set of genes that are unchanged in expression, usually obtained from accompanying RNA-seq data, and extrapolating to normalize the genome-wide chromatin accessibility profile. We demonstrate the effectiveness of IGN in analyzing central memory CD8+ T cell activation, a system with anticipated global reprogramming of chromatin and gene expression, and show that IGN outperforms existing methods. As the first chromatin accessibility normalization method that accounts for global differences, IGN can be widely applied to differential ATAC-seq and DNase-seq analysis. The package and source code are available on GitHub at https://github.com/zang-lab/IGN.http://www.sciencedirect.com/science/article/pii/S2001037025000170Chromatin accessibilityNormalizationDifferential analysisATAC-seqDNase-seq |
| spellingShingle | Shengen Shawn Hu Hai-Hui Xue Chongzhi Zang IGN: Invariable gene set-based normalization for chromatin accessibility profile data analysis Computational and Structural Biotechnology Journal Chromatin accessibility Normalization Differential analysis ATAC-seq DNase-seq |
| title | IGN: Invariable gene set-based normalization for chromatin accessibility profile data analysis |
| title_full | IGN: Invariable gene set-based normalization for chromatin accessibility profile data analysis |
| title_fullStr | IGN: Invariable gene set-based normalization for chromatin accessibility profile data analysis |
| title_full_unstemmed | IGN: Invariable gene set-based normalization for chromatin accessibility profile data analysis |
| title_short | IGN: Invariable gene set-based normalization for chromatin accessibility profile data analysis |
| title_sort | ign invariable gene set based normalization for chromatin accessibility profile data analysis |
| topic | Chromatin accessibility Normalization Differential analysis ATAC-seq DNase-seq |
| url | http://www.sciencedirect.com/science/article/pii/S2001037025000170 |
| work_keys_str_mv | AT shengenshawnhu igninvariablegenesetbasednormalizationforchromatinaccessibilityprofiledataanalysis AT haihuixue igninvariablegenesetbasednormalizationforchromatinaccessibilityprofiledataanalysis AT chongzhizang igninvariablegenesetbasednormalizationforchromatinaccessibilityprofiledataanalysis |