Yih-Chii Hwang1, Chiao-Feng Lin2, Otto Valladares2, John Malamon2, Pavel P Kuksa2, Qi Zheng1, Brian D Gregory2, Li-San Wang3. 1. Genomics and Computational Biology Graduate Program, University of Pennsylvania, Institute for Biomedical Informatics, University of Pennsylvania, Department of Pathology and Laboratory Medicine, University of Pennsylvania and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104. 2. Genomics and Computational Biology Graduate Program, University of Pennsylvania, Institute for Biomedical Informatics, University of Pennsylvania, Department of Pathology and Laboratory Medicine, University of Pennsylvania and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104 Genomics and Computational Biology Graduate Program, University of Pennsylvania, Institute for Biomedical Informatics, University of Pennsylvania, Department of Pathology and Laboratory Medicine, University of Pennsylvania and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104. 3. Genomics and Computational Biology Graduate Program, University of Pennsylvania, Institute for Biomedical Informatics, University of Pennsylvania, Department of Pathology and Laboratory Medicine, University of Pennsylvania and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104 Genomics and Computational Biology Graduate Program, University of Pennsylvania, Institute for Biomedical Informatics, University of Pennsylvania, Department of Pathology and Laboratory Medicine, University of Pennsylvania and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104 Genomics and Computational Biology Graduate Program, University of Pennsylvania, Institute for Biomedical Informatics, University of Pennsylvania, Department of Pathology and Laboratory Medicine, University of Pennsylvania and Department of Biology, University of Pennsylvania, Philadelphia, PA 19104.
Abstract
UNLABELLED: We implemented a high-throughput identification pipeline for promoter interacting enhancer element to streamline the workflow from mapping raw Hi-C reads, identifying DNA-DNA interacting fragments with high confidence and quality control, detecting histone modifications and DNase hypersensitive enrichments in putative enhancer elements, to ultimately extracting possible intra- and inter-chromosomal enhancer-target gene relationships. AVAILABILITY AND IMPLEMENTATION: This software package is designed to run on high-performance computing clusters with Oracle Grid Engine. The source code is freely available under the MIT license for academic and nonprofit use. The source code and instructions are available at the Wang lab website (http://wanglab.pcbi.upenn.edu/hippie/). It is also provided as an Amazon Machine Image to be used directly on Amazon Cloud with minimal installation. CONTACT: lswang@mail.med.upenn.edu or bdgregor@sas.upenn.edu SUPPLEMENTARY INFORMATION: Supplementary Material is available at Bioinformatics online.
UNLABELLED: We implemented a high-throughput identification pipeline for promoter interacting enhancer element to streamline the workflow from mapping raw Hi-C reads, identifying DNA-DNA interacting fragments with high confidence and quality control, detecting histone modifications and DNase hypersensitive enrichments in putative enhancer elements, to ultimately extracting possible intra- and inter-chromosomal enhancer-target gene relationships. AVAILABILITY AND IMPLEMENTATION: This software package is designed to run on high-performance computing clusters with Oracle Grid Engine. The source code is freely available under the MIT license for academic and nonprofit use. The source code and instructions are available at the Wang lab website (http://wanglab.pcbi.upenn.edu/hippie/). It is also provided as an Amazon Machine Image to be used directly on Amazon Cloud with minimal installation. CONTACT: lswang@mail.med.upenn.edu or bdgregor@sas.upenn.edu SUPPLEMENTARY INFORMATION: Supplementary Material is available at Bioinformatics online.
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