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Accounting for GC-content bias reduces systematic errors and batch effects in ChIP-Seq data
View ORCID ProfileMingxiang Teng, View ORCID ProfileRafael A. Irizarry
doi: https://doi.org/10.1101/090704
Mingxiang Teng
1Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA, United States
2Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, United States
Rafael A. Irizarry
1Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA, United States
2Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, United States

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Posted January 15, 2017.
Accounting for GC-content bias reduces systematic errors and batch effects in ChIP-Seq data
Mingxiang Teng, Rafael A. Irizarry
bioRxiv 090704; doi: https://doi.org/10.1101/090704
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