Novel genomes are today often annotated by small consortia or individuals whose background is not from bioinformatics.This audience requires tools that are easy to use.Such need has been addressed by several genome an...Novel genomes are today often annotated by small consortia or individuals whose background is not from bioinformatics.This audience requires tools that are easy to use.Such need has been addressed by several genome annotation tools and pipelines.Visualizing resulting annotation is a crucial step of quality control.The UCSC Genome Browser is a powerful and popular genome visualization tool.Assembly Hubs,which can be hosted on any publicly available web server,allow browsing genomes via UCSC Genome Browser servers.The steps for creating custom Assembly Hubs are well documented and the required tools are publicly available.However,the number of steps for creating a novel Assembly Hub is large.In some cases,the format of input files needs to be adapted,which is a difficult task for scientists without programming background.Here,we describe Make Hub,a novel command line tool that generates Assembly Hubs for the UCSC Genome Browser in a fully automated fashion.The pipeline also allows extending previously created Hubs by additional tracks.Make Hub is freely available for downloading at https://github.com/Gaius-Augustus/Make Hub.展开更多
The Network Makeup Artist(NORMA) is a web tool for interactive network annotation visualization and topological analysis, able to handle multiple networks and annotations simultaneously. Precalculated annotations(e.g....The Network Makeup Artist(NORMA) is a web tool for interactive network annotation visualization and topological analysis, able to handle multiple networks and annotations simultaneously. Precalculated annotations(e.g., Gene Ontology, Pathway enrichment, community detection,or clustering results) can be uploaded and visualized in a network, either as colored pie-chart nodes or as color-filled areas in a 2D/3D Venn-diagram-like style. In the case where no annotation exists,algorithms for automated community detection are offered. Users can adjust the network views using standard layout algorithms or allow NORMA to slightly modify them for visually better group separation. Once a network view is set, users can interactively select and highlight any group of interest in order to generate publication-ready figures. Briefy, with NORMA, users can encode three types of information simultaneously. These are 1) the network, 2) the communities or annotations of interest, and 3) node categories or expression values. Finally, NORMA offers basic topological analysis and direct topological comparison across any of the selected networks. NORMA service is available at http://norma.pavlopouloslab.info, whereas the code is available at https://github.com/Pavlopoulos Lab/NORMA.展开更多
Gene spectrum analysis has shown that gene expression and signaling pathways change dramatically after spinal cord injury,which may affect the microenvironment of the damaged site.Microarray analysis provides a new op...Gene spectrum analysis has shown that gene expression and signaling pathways change dramatically after spinal cord injury,which may affect the microenvironment of the damaged site.Microarray analysis provides a new opportunity for investigating diagnosis,treatment,and prognosis of spinal cord injury.However,differentially expressed genes are not consistent among studies,and many key genes and signaling pathways have not yet been accurately studied.GSE5296 was retrieved from the Gene Expression Omnibus DataSet.Differentially expressed genes were obtained using R/Bioconductor software(expression changed at least two-fold;P < 0.05).Database for Annotation,Visualization and Integrated Discovery was used for functional annotation of differentially expressed genes and Animal Transcription Factor Database for predicting potential transcription factors.The resulting transcription regulatory protein interaction network was mapped to screen representative genes and investigate their diagnostic and therapeutic value for disease.In total,this study identified 109 genes that were upregulated and 30 that were downregulated at 0.5,4,and 24 hours,and 3,7,and 28 days after spinal cord injury.The number of downregulated genes was smaller than the number of upregulated genes at each time point.Database for Annotation,Visualization and Integrated Discovery analysis found that many inflammation-related pathways were upregulated in injured spinal cord.Additionally,expression levels of these inflammation-related genes were maintained for at least 28 days.Moreover,399 regulation modes and 77 nodes were shown in the protein-protein interaction network of upregulated differentially expressed genes.Among the 10 upregulated differentially expressed genes with the highest degrees of distribution,six genes were transcription factors.Among these transcription factors,ATF3 showed the greatest change.ATF3 was upregulated within 30 minutes,and its expression levels remained high at28 days after spinal cord injury.These key genes screened by bioin展开更多
Objective： Identification of colorectal cancer （CRC） metastasis genes is one of the most important issues in CRC research. For the purpose of mining CRC metastasis-associated genes, an integrated analysis of mJcroa...Objective： Identification of colorectal cancer （CRC） metastasis genes is one of the most important issues in CRC research. For the purpose of mining CRC metastasis-associated genes, an integrated analysis of mJcroarray data was presented, by combined with evidence acquired from comparative genornic hybridization （CGH） data. Methods： Gene expression profile data of CRC samples were obtained at Gene Expression Omnibus （GEO） website. The 15 important chromosomal aberration sites detected by using CGH technology were used for integrated genomic and transcriptomic analysis. Significant Analysis of Microarray （SAM） was used to detect significantly differentially expressed genes across the whole genome. The overlapping genes were selected in their corresponding chromosomal aberration regions, and analyzed by using the Database for Annotation, Visualization and Integrated Discovery （DAVID）. Finally, SVM-T-RFE gene selection algorithm was applied to identify ted genes in CRC. Results： A minimum gene set was obtained with the minimum number [14] of genes, and the highest classification accuracy （100%） in both PRI and META datasets. A fraction of selected genes are associated with CRC or its metastasis. Conclusions- Our results demonstrated that integration analysis is an effective strategy for mining cancer- associated genes.展开更多
基金US National Institutes of Health(Grant No.HG000783),gave rise to the development of MakeHubUniversitat Greifswald,Germany.
文摘Novel genomes are today often annotated by small consortia or individuals whose background is not from bioinformatics.This audience requires tools that are easy to use.Such need has been addressed by several genome annotation tools and pipelines.Visualizing resulting annotation is a crucial step of quality control.The UCSC Genome Browser is a powerful and popular genome visualization tool.Assembly Hubs,which can be hosted on any publicly available web server,allow browsing genomes via UCSC Genome Browser servers.The steps for creating custom Assembly Hubs are well documented and the required tools are publicly available.However,the number of steps for creating a novel Assembly Hub is large.In some cases,the format of input files needs to be adapted,which is a difficult task for scientists without programming background.Here,we describe Make Hub,a novel command line tool that generates Assembly Hubs for the UCSC Genome Browser in a fully automated fashion.The pipeline also allows extending previously created Hubs by additional tracks.Make Hub is freely available for downloading at https://github.com/Gaius-Augustus/Make Hub.
基金supported by the Operational Program Competitiveness,Entrepreneurship,Innovation,NSRF 2014-2020 (Grant No.MIS 5002562,co-financed by Greece and the European Union (European Regional Development Fund)supported by the Hellenic Foundation for Research and Innovation (HFRI) under the"First Call for HFRI Research Projects to support Faculty members and Researchers and the procurement of high-cost research equipment grant"(Grant No.1855-BOLOGNA)+2 种基金supported by the Action Strengthening Human ResourcesEducation and Lifelong Learning,2014-2020,co-funded by the European Social Fund (ESF) and the Greek State (Grant No.MIS 5000432)supported by a grant from the Stavros Niarchos Foundation to the Biomedical Sciences Research Center"Alexander Fleming",as part of the initiative of the Foundation to support the Greek research center ecosystem
文摘The Network Makeup Artist(NORMA) is a web tool for interactive network annotation visualization and topological analysis, able to handle multiple networks and annotations simultaneously. Precalculated annotations(e.g., Gene Ontology, Pathway enrichment, community detection,or clustering results) can be uploaded and visualized in a network, either as colored pie-chart nodes or as color-filled areas in a 2D/3D Venn-diagram-like style. In the case where no annotation exists,algorithms for automated community detection are offered. Users can adjust the network views using standard layout algorithms or allow NORMA to slightly modify them for visually better group separation. Once a network view is set, users can interactively select and highlight any group of interest in order to generate publication-ready figures. Briefy, with NORMA, users can encode three types of information simultaneously. These are 1) the network, 2) the communities or annotations of interest, and 3) node categories or expression values. Finally, NORMA offers basic topological analysis and direct topological comparison across any of the selected networks. NORMA service is available at http://norma.pavlopouloslab.info, whereas the code is available at https://github.com/Pavlopoulos Lab/NORMA.
基金supported by the Natural Science Foundation of Shaanxi Province of China,No.2018JQ8029(to LG)
文摘Gene spectrum analysis has shown that gene expression and signaling pathways change dramatically after spinal cord injury,which may affect the microenvironment of the damaged site.Microarray analysis provides a new opportunity for investigating diagnosis,treatment,and prognosis of spinal cord injury.However,differentially expressed genes are not consistent among studies,and many key genes and signaling pathways have not yet been accurately studied.GSE5296 was retrieved from the Gene Expression Omnibus DataSet.Differentially expressed genes were obtained using R/Bioconductor software(expression changed at least two-fold;P < 0.05).Database for Annotation,Visualization and Integrated Discovery was used for functional annotation of differentially expressed genes and Animal Transcription Factor Database for predicting potential transcription factors.The resulting transcription regulatory protein interaction network was mapped to screen representative genes and investigate their diagnostic and therapeutic value for disease.In total,this study identified 109 genes that were upregulated and 30 that were downregulated at 0.5,4,and 24 hours,and 3,7,and 28 days after spinal cord injury.The number of downregulated genes was smaller than the number of upregulated genes at each time point.Database for Annotation,Visualization and Integrated Discovery analysis found that many inflammation-related pathways were upregulated in injured spinal cord.Additionally,expression levels of these inflammation-related genes were maintained for at least 28 days.Moreover,399 regulation modes and 77 nodes were shown in the protein-protein interaction network of upregulated differentially expressed genes.Among the 10 upregulated differentially expressed genes with the highest degrees of distribution,six genes were transcription factors.Among these transcription factors,ATF3 showed the greatest change.ATF3 was upregulated within 30 minutes,and its expression levels remained high at28 days after spinal cord injury.These key genes screened by bioin
基金supported by a grant from the National Natural Science Foundation of China(Grant No.61373057)a grant from the Zhejiang Provincial Natural Science Foundation of China(Grant No.Y1110763)
文摘Objective： Identification of colorectal cancer （CRC） metastasis genes is one of the most important issues in CRC research. For the purpose of mining CRC metastasis-associated genes, an integrated analysis of mJcroarray data was presented, by combined with evidence acquired from comparative genornic hybridization （CGH） data. Methods： Gene expression profile data of CRC samples were obtained at Gene Expression Omnibus （GEO） website. The 15 important chromosomal aberration sites detected by using CGH technology were used for integrated genomic and transcriptomic analysis. Significant Analysis of Microarray （SAM） was used to detect significantly differentially expressed genes across the whole genome. The overlapping genes were selected in their corresponding chromosomal aberration regions, and analyzed by using the Database for Annotation, Visualization and Integrated Discovery （DAVID）. Finally, SVM-T-RFE gene selection algorithm was applied to identify ted genes in CRC. Results： A minimum gene set was obtained with the minimum number [14] of genes, and the highest classification accuracy （100%） in both PRI and META datasets. A fraction of selected genes are associated with CRC or its metastasis. Conclusions- Our results demonstrated that integration analysis is an effective strategy for mining cancer- associated genes.
