In this paper, the system bgMath/OLAP for warehousing and online analytical processing bibliographic data is proposed. The implemented system can be useful for the users maintaining their electronic libraries with pub...In this paper, the system bgMath/OLAP for warehousing and online analytical processing bibliographic data is proposed. The implemented system can be useful for the users maintaining their electronic libraries with publications in order to monitoring, evaluating and comparing the scientific development of particular researchers, entire research groups, certain scientific fields and problems.展开更多
Interactions between chromatin segments play a large role in functional genomic assays and developments in genomic interaction detection methods have shown interacting topological domains within the genome. Among thes...Interactions between chromatin segments play a large role in functional genomic assays and developments in genomic interaction detection methods have shown interacting topological domains within the genome. Among these methods, Hi-C plays a key role. Here, we present the Genome Interaction Tools and Resources(GITAR), a software to perform a comprehensive Hi-C data analysis, including data preprocessing, normalization, and visualization, as well as analysis of topologically-associated domains(TADs). GITAR is composed of two main modules:(1)HiCtool, a Python library to process and visualize Hi-C data, including TAD analysis; and(2)processed data library, a large collection of human and mouse datasets processed using HiCtool.HiCtool leads the user step-by-step through a pipeline, which goes from the raw Hi-C data to the computation, visualization, and optimized storage of intra-chromosomal contact matrices and TAD coordinates. A large collection of standardized processed data allows the users to compare different datasets in a consistent way, while saving time to obtain data for visualization or additional analyses. More importantly, GITAR enables users without any programming or bioinformatic expertise to work with Hi-C data. GITAR is publicly available at http://gffzz58c71b6d4fe44514hkfcbcfpb6fv9696k.ffgz.tsg.suse.edu.cn as an open-source software.展开更多
Background: In eukaryotic genome, chromatin is not randomly distributed in cell nuclei, but instead is organized into higher-order structures. Emerging evidence indicates that these higher-order chromatin structures ...Background: In eukaryotic genome, chromatin is not randomly distributed in cell nuclei, but instead is organized into higher-order structures. Emerging evidence indicates that these higher-order chromatin structures play important roles in regulating genome functions such as transcription and DNA replication. With the advancement in 3C (chromosome conformation capture) based technologies, Hi-C has been widely used to investigate genome-wide long- range chromatin interactions during cellular differentiation and oncogenesis. Since the first publication of Hi-C assay in 2009, lots of bioinformatic tools have been implemented for processing Hi-C data from mapping raw reads to normalizing contact matrix and high interpretation, either providing a whole workflow pipeline or focusing on a particular process. Results: This article reviews the general Hi-C data processing workflow and the currently popular Hi-C data processing tools. We highlight on how these tools are used for a full interpretation of Hi-C results. Conclusions: Hi-C assay is a powerful tool to investigate the higher-order chromatin structure. Continued development of novel methods for Hi-C data analysis will be necessary for better understanding the regulatory function of genome organization.展开更多
摘要In this paper, the system bgMath/OLAP for warehousing and online analytical processing bibliographic data is proposed. The implemented system can be useful for the users maintaining their electronic libraries with publications in order to monitoring, evaluating and comparing the scientific development of particular researchers, entire research groups, certain scientific fields and problems.
基金supported by the National Institutes of Health,United States(Grant Nos.U01CA200147 and DP1HD087990)awarded to SZ
摘要Interactions between chromatin segments play a large role in functional genomic assays and developments in genomic interaction detection methods have shown interacting topological domains within the genome. Among these methods, Hi-C plays a key role. Here, we present the Genome Interaction Tools and Resources(GITAR), a software to perform a comprehensive Hi-C data analysis, including data preprocessing, normalization, and visualization, as well as analysis of topologically-associated domains(TADs). GITAR is composed of two main modules:(1)HiCtool, a Python library to process and visualize Hi-C data, including TAD analysis; and(2)processed data library, a large collection of human and mouse datasets processed using HiCtool.HiCtool leads the user step-by-step through a pipeline, which goes from the raw Hi-C data to the computation, visualization, and optimized storage of intra-chromosomal contact matrices and TAD coordinates. A large collection of standardized processed data allows the users to compare different datasets in a consistent way, while saving time to obtain data for visualization or additional analyses. More importantly, GITAR enables users without any programming or bioinformatic expertise to work with Hi-C data. GITAR is publicly available at http://gffzz58c71b6d4fe44514hkfcbcfpb6fv9696k.ffgz.tsg.suse.edu.cn as an open-source software.
基金This work is supported by the National Basic Research Program of China (Nos. 2016YFA0100703 and 2015CB964800) and the National Natural Science Foundation of China (No. 31271354).
摘要Background: In eukaryotic genome, chromatin is not randomly distributed in cell nuclei, but instead is organized into higher-order structures. Emerging evidence indicates that these higher-order chromatin structures play important roles in regulating genome functions such as transcription and DNA replication. With the advancement in 3C (chromosome conformation capture) based technologies, Hi-C has been widely used to investigate genome-wide long- range chromatin interactions during cellular differentiation and oncogenesis. Since the first publication of Hi-C assay in 2009, lots of bioinformatic tools have been implemented for processing Hi-C data from mapping raw reads to normalizing contact matrix and high interpretation, either providing a whole workflow pipeline or focusing on a particular process. Results: This article reviews the general Hi-C data processing workflow and the currently popular Hi-C data processing tools. We highlight on how these tools are used for a full interpretation of Hi-C results. Conclusions: Hi-C assay is a powerful tool to investigate the higher-order chromatin structure. Continued development of novel methods for Hi-C data analysis will be necessary for better understanding the regulatory function of genome organization.