GeneCloudOmics: A Data Analytic Cloud Platform for High-Throughput Gene Expression Analysis
Gene expression profiling techniques, such as DNA microarray and RNA-Sequencing, have provided significant impact on our understanding of biological systems. They contribute to almost all aspects of biomedical research, including studying developmental biology, host-parasite relationships, disease p...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2021-11-01
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| Series: | Frontiers in Bioinformatics |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fbinf.2021.693836/full |
| _version_ | 1818937082402308096 |
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| author | Mohamed Helmy Mohamed Helmy Rahul Agrawal Javed Ali Mohamed Soudy Thuy Tien Bui Kumar Selvarajoo Kumar Selvarajoo Kumar Selvarajoo |
| author_facet | Mohamed Helmy Mohamed Helmy Rahul Agrawal Javed Ali Mohamed Soudy Thuy Tien Bui Kumar Selvarajoo Kumar Selvarajoo Kumar Selvarajoo |
| author_sort | Mohamed Helmy |
| collection | DOAJ |
| description | Gene expression profiling techniques, such as DNA microarray and RNA-Sequencing, have provided significant impact on our understanding of biological systems. They contribute to almost all aspects of biomedical research, including studying developmental biology, host-parasite relationships, disease progression and drug effects. However, the high-throughput data generations present challenges for many wet experimentalists to analyze and take full advantage of such rich and complex data. Here we present GeneCloudOmics, an easy-to-use web server for high-throughput gene expression analysis that extends the functionality of our previous ABioTrans with several new tools, including protein datasets analysis, and a web interface. GeneCloudOmics allows both microarray and RNA-Seq data analysis with a comprehensive range of data analytics tools in one package that no other current standalone software or web-based tool can do. In total, GeneCloudOmics provides the user access to 23 different data analytical and bioinformatics tasks including reads normalization, scatter plots, linear/non-linear correlations, PCA, clustering (hierarchical, k-means, t-SNE, SOM), differential expression analyses, pathway enrichments, evolutionary analyses, pathological analyses, and protein-protein interaction (PPI) identifications. Furthermore, GeneCloudOmics allows the direct import of gene expression data from the NCBI Gene Expression Omnibus database. The user can perform all tasks rapidly through an intuitive graphical user interface that overcomes the hassle of coding, installing tools/packages/libraries and dealing with operating systems compatibility and version issues, complications that make data analysis tasks challenging for biologists. Thus, GeneCloudOmics is a one-stop open-source tool for gene expression data analysis and visualization. It is freely available at http://combio-sifbi.org/GeneCloudOmics. |
| first_indexed | 2024-12-20T05:46:18Z |
| format | Article |
| id | doaj.art-299125d1b77446728f33b0e71e48ac52 |
| institution | Directory Open Access Journal |
| issn | 2673-7647 |
| language | English |
| last_indexed | 2024-12-20T05:46:18Z |
| publishDate | 2021-11-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Bioinformatics |
| spelling | doaj.art-299125d1b77446728f33b0e71e48ac522022-12-21T19:51:18ZengFrontiers Media S.A.Frontiers in Bioinformatics2673-76472021-11-01110.3389/fbinf.2021.693836693836GeneCloudOmics: A Data Analytic Cloud Platform for High-Throughput Gene Expression AnalysisMohamed Helmy0Mohamed Helmy1Rahul Agrawal2Javed Ali3Mohamed Soudy4Thuy Tien Bui5Kumar Selvarajoo6Kumar Selvarajoo7Kumar Selvarajoo8Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), Singapore, SingaporeDepartment of Computer Science, Lakehead University, Thunder Bay, ON, CanadaDepartment of Geology and Geophysics, Indian Institute of Technology (IIT) Kharagpur, Kharagpur, IndiaDepartment of Geology and Geophysics, Indian Institute of Technology (IIT) Kharagpur, Kharagpur, IndiaProteomics and Metabolomics Unit, Children Cancer Hospital (CCHE-57357), Cairo, EgyptBioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), Singapore, SingaporeBioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), Singapore, SingaporeSingapore Institute of Food and Biotechnology Innovation (SIFBI), Agency for Science, Technology and Research (A*STAR), Singapore, SingaporeSynthetic Biology for Clinical and Technological Innovation (SynCTI), National University of Singapore (NUS), Singapore, SingaporeGene expression profiling techniques, such as DNA microarray and RNA-Sequencing, have provided significant impact on our understanding of biological systems. They contribute to almost all aspects of biomedical research, including studying developmental biology, host-parasite relationships, disease progression and drug effects. However, the high-throughput data generations present challenges for many wet experimentalists to analyze and take full advantage of such rich and complex data. Here we present GeneCloudOmics, an easy-to-use web server for high-throughput gene expression analysis that extends the functionality of our previous ABioTrans with several new tools, including protein datasets analysis, and a web interface. GeneCloudOmics allows both microarray and RNA-Seq data analysis with a comprehensive range of data analytics tools in one package that no other current standalone software or web-based tool can do. In total, GeneCloudOmics provides the user access to 23 different data analytical and bioinformatics tasks including reads normalization, scatter plots, linear/non-linear correlations, PCA, clustering (hierarchical, k-means, t-SNE, SOM), differential expression analyses, pathway enrichments, evolutionary analyses, pathological analyses, and protein-protein interaction (PPI) identifications. Furthermore, GeneCloudOmics allows the direct import of gene expression data from the NCBI Gene Expression Omnibus database. The user can perform all tasks rapidly through an intuitive graphical user interface that overcomes the hassle of coding, installing tools/packages/libraries and dealing with operating systems compatibility and version issues, complications that make data analysis tasks challenging for biologists. Thus, GeneCloudOmics is a one-stop open-source tool for gene expression data analysis and visualization. It is freely available at http://combio-sifbi.org/GeneCloudOmics.https://www.frontiersin.org/articles/10.3389/fbinf.2021.693836/fullOMICS datagene expression analysisbioinformaticsmicroarrayRNA-seqtranscriptomics |
| spellingShingle | Mohamed Helmy Mohamed Helmy Rahul Agrawal Javed Ali Mohamed Soudy Thuy Tien Bui Kumar Selvarajoo Kumar Selvarajoo Kumar Selvarajoo GeneCloudOmics: A Data Analytic Cloud Platform for High-Throughput Gene Expression Analysis Frontiers in Bioinformatics OMICS data gene expression analysis bioinformatics microarray RNA-seq transcriptomics |
| title | GeneCloudOmics: A Data Analytic Cloud Platform for High-Throughput Gene Expression Analysis |
| title_full | GeneCloudOmics: A Data Analytic Cloud Platform for High-Throughput Gene Expression Analysis |
| title_fullStr | GeneCloudOmics: A Data Analytic Cloud Platform for High-Throughput Gene Expression Analysis |
| title_full_unstemmed | GeneCloudOmics: A Data Analytic Cloud Platform for High-Throughput Gene Expression Analysis |
| title_short | GeneCloudOmics: A Data Analytic Cloud Platform for High-Throughput Gene Expression Analysis |
| title_sort | genecloudomics a data analytic cloud platform for high throughput gene expression analysis |
| topic | OMICS data gene expression analysis bioinformatics microarray RNA-seq transcriptomics |
| url | https://www.frontiersin.org/articles/10.3389/fbinf.2021.693836/full |
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