Dataset Information

HIPPIE: a high-throughput identification pipeline for promoter interacting enhancer elements.

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.

SUBMITTER: Hwang YC

PROVIDER: S-EPMC4393516 | biostudies-literature | 2015 Apr

REPOSITORIES: biostudies-literature

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Publications

HIPPIE: a high-throughput identification pipeline for promoter interacting enhancer elements.

Hwang Yih-Chii YC Lin Chiao-Feng CF Valladares Otto O Malamon John J Kuksa Pavel P PP Zheng Qi Q Gregory Brian D BD Wang Li-San LS

Bioinformatics (Oxford, England) 20141204 8

<h4>Unlabelled</h4>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.<h4>Availability and implementation</h4>This ...[more]

PMID: 25480377

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Project description:BACKGROUND:Bioinformatics tools designed to identify lentiviral or retroviral vector insertion sites in the genome of host cells are used to address the safety and long-term efficacy of hematopoietic stem cell gene therapy applications and to study the clonal dynamics of hematopoietic reconstitution. The increasing number of gene therapy clinical trials combined with the increasing amount of Next Generation Sequencing data, aimed at identifying integration sites, require both highly accurate and efficient computational software able to correctly process "big data" in a reasonable computational time. RESULTS:Here we present VISPA2 (Vector Integration Site Parallel Analysis, version 2), the latest optimized computational pipeline for integration site identification and analysis with the following features: (1) the sequence analysis for the integration site processing is fully compliant with paired-end reads and includes a sequence quality filter before and after the alignment on the target genome; (2) an heuristic algorithm to reduce false positive integration sites at nucleotide level to reduce the impact of Polymerase Chain Reaction or trimming/alignment artifacts; (3) a classification and annotation module for integration sites; (4) a user friendly web interface as researcher front-end to perform integration site analyses without computational skills; (5) the time speedup of all steps through parallelization (Hadoop free). CONCLUSIONS:We tested VISPA2 performances using simulated and real datasets of lentiviral vector integration sites, previously obtained from patients enrolled in a hematopoietic stem cell gene therapy clinical trial and compared the results with other preexisting tools for integration site analysis. On the computational side, VISPA2 showed a > 6-fold speedup and improved precision and recall metrics (1 and 0.97 respectively) compared to previously developed computational pipelines. These performances indicate that VISPA2 is a fast, reliable and user-friendly tool for integration site analysis, which allows gene therapy integration data to be handled in a cost and time effective fashion. Moreover, the web access of VISPA2 ( http://openserver.itb.cnr.it/vispa/ ) ensures accessibility and ease of usage to researches of a complex analytical tool. We released the source code of VISPA2 in a public repository ( https://bitbucket.org/andreacalabria/vispa2 ).

Dataset Information

HIPPIE: a high-throughput identification pipeline for promoter interacting enhancer elements.

Unlabelled

Availability and implementation

Contact

Supplementary information

Publications

HIPPIE: a high-throughput identification pipeline for promoter interacting enhancer elements.

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