ChIPseqSpikeInFree: a ChIP-seq normalization approach to reveal global changes in histone modifications without spike-in | Zendy

Hongjian Jin | Zendy; Lawryn H. Kasper | Zendy; Jon D. Larson | Zendy; Gang Wu | Zendy; Suzanne J. Baker | Zendy; Jinghui Zhang | Zendy; Yiping Fan | Zendy

Open Access

ChIPseqSpikeInFree: a ChIP-seq normalization approach to reveal global changes in histone modifications without spike-in

Author(s) -

Hongjian Jin,

Lawryn H. Kasper,

Jon D. Larson,

Gang Wu,

Suzanne J. Baker,

Jinghui Zhang,

Yiping Fan

Publication year - 2019

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btz720

Subject(s) - normalization (sociology) , spike (software development) , computer science , histone , computational biology , pattern recognition (psychology) , artificial intelligence , biology , genetics , gene , software engineering , sociology , anthropology

The traditional reads per million normalization method is inappropriate for the evaluation of ChIP-seq data when treatments or mutations have global effects. Changes in global levels of histone modifications can be detected with exogenous reference spike-in controls. However, most ChIP-seq studies overlook the normalization that must be corrected with spike-in. A method that retrospectively renormalizes datasets without spike-in is lacking.

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