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Reducing False Positives in CRISPR/Cas9 Screens from Copy Number Variations

Alexander Wu, Tengfei Xiao, Teng Fei, X. Shirley Liu, View ORCID ProfileWei Li
doi: https://doi.org/10.1101/247031
Alexander Wu
1Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard School of Public Health, Boston, MA 02215, USA
2Program in Computational Biology and Quantitative Genetics, Harvard School of Public Health, Boston, MA 02215, USA
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Tengfei Xiao
3Division of Molecular and Cellular Oncology, Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA
4Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA 02215 USA
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Teng Fei
5College of Life and Health Sciences, Northeastern University, Shenyang 110819, People’s Republic of China
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X. Shirley Liu
1Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard School of Public Health, Boston, MA 02215, USA
4Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA 02215 USA
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Wei Li
1Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard School of Public Health, Boston, MA 02215, USA
4Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA 02215 USA
6Center for Generic Medicine Research, Children’s National Health System, Washington, DC 20010, USA
7Department of Genomics and Precision Medicine, The George Washington School of Medicine and Health Sciences, Washington, DC 20010, USA
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Abstract

CRISPR/Cas9 knockout screens have been widely used to interrogate gene functions across a wide range of cell systems. However, the screening outcome is biased in amplified genomic regions, due to the ability of the Cas9 nuclease to induce multiple double-stranded breaks and strong DNA damage responses at these regions. We developed algorithms to correct biases associated with copy number variations (CNV), even when the CNV profiles are unknown. We demonstrated that our methods effectively reduced false positives in amplified regions while preserving signals of true positives. In addition, we developed a sliding window approach to estimate regions of high copy numbers for cases in which CNV information is not available. These copy number estimations can subsequently be used to effectively correct CNV-related biases in CRISPR screening experiments. Our approach is integrated into the existing MAGeCK/MAGeCK-VISPR analysis pipelines and provides a convenient framework to improve the precision of CRISPR screening results.

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Posted January 11, 2018.
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Reducing False Positives in CRISPR/Cas9 Screens from Copy Number Variations
Alexander Wu, Tengfei Xiao, Teng Fei, X. Shirley Liu, Wei Li
bioRxiv 247031; doi: https://doi.org/10.1101/247031
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Reducing False Positives in CRISPR/Cas9 Screens from Copy Number Variations
Alexander Wu, Tengfei Xiao, Teng Fei, X. Shirley Liu, Wei Li
bioRxiv 247031; doi: https://doi.org/10.1101/247031

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