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MAPS: model-based analysis of long-range chromatin interactions from PLAC-seq and HiChIP experiments

Ivan Juric, Miao Yu, Armen Abnousi, Ramya Raviram, Rongxin Fang, Yuan Zhao, Yanxiao Zhang, Yuchen Yang, Yun Li, Bing Ren, Ming Hu
doi: https://doi.org/10.1101/411835
Ivan Juric
1Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH 44195, USA
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Miao Yu
2Ludwig Institute for Cancer Research, La Jolla, CA 92093, USA
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Armen Abnousi
1Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH 44195, USA
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Ramya Raviram
2Ludwig Institute for Cancer Research, La Jolla, CA 92093, USA
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Rongxin Fang
2Ludwig Institute for Cancer Research, La Jolla, CA 92093, USA
3Bioinformatics and Systems Biology Graduate Program, University of California, San Diego, La Jolla, CA 92093, USA
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Yuan Zhao
2Ludwig Institute for Cancer Research, La Jolla, CA 92093, USA
3Bioinformatics and Systems Biology Graduate Program, University of California, San Diego, La Jolla, CA 92093, USA
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Yanxiao Zhang
2Ludwig Institute for Cancer Research, La Jolla, CA 92093, USA
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Yuchen Yang
4Departments of Genetics, Biostatistics, and Computer Science, University of North Carolina, Chapel Hill, NC 27599, USA
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Yun Li
4Departments of Genetics, Biostatistics, and Computer Science, University of North Carolina, Chapel Hill, NC 27599, USA
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Bing Ren
2Ludwig Institute for Cancer Research, La Jolla, CA 92093, USA
5Department of Cellular and Molecular Medicine, Center for Epigenomics, University of California, San Diego School of Medicine, 9500 Gilman Drive, La Jolla, CA 92093, USA
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  • For correspondence: hum@ccf.org biren@ucsd.edu
Ming Hu
1Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH 44195, USA
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  • For correspondence: hum@ccf.org biren@ucsd.edu
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Abstract

Hi-C and chromatin immunoprecipitation (ChIP) have been combined to identify long-range chromatin interactions genome-wide at reduced cost and enhanced resolution, but extracting the information from the resulting datasets has been challenging. Here we describe a computational method, MAPS, Model-based Analysis of PLAC-seq and HiChIP, to process the data from such experiments and identify long-range chromatin interactions. MAPS adopts a zero-truncated Poisson regression framework to explicitly remove systematic biases in the PLAC-seq and HiChIP datasets, and then uses the normalized chromatin contact frequencies to identify significant chromatin interactions anchored at genomic regions bound by the protein of interest. MAPS shows superior performance over existing software tools in analysis of chromatin interactions centered on cohesin, CTCF and H3K4me3 associated regions in multiple cell types. MAPS is freely available at https://github.com/ijuric/MAPS.

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Posted September 08, 2018.
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MAPS: model-based analysis of long-range chromatin interactions from PLAC-seq and HiChIP experiments
Ivan Juric, Miao Yu, Armen Abnousi, Ramya Raviram, Rongxin Fang, Yuan Zhao, Yanxiao Zhang, Yuchen Yang, Yun Li, Bing Ren, Ming Hu
bioRxiv 411835; doi: https://doi.org/10.1101/411835
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MAPS: model-based analysis of long-range chromatin interactions from PLAC-seq and HiChIP experiments
Ivan Juric, Miao Yu, Armen Abnousi, Ramya Raviram, Rongxin Fang, Yuan Zhao, Yanxiao Zhang, Yuchen Yang, Yun Li, Bing Ren, Ming Hu
bioRxiv 411835; doi: https://doi.org/10.1101/411835

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