Residential College | false |
Status | 已發表Published |
Empowering biologists to decode omics data: the Genekitr R package and web server | |
Yunze Liu1,2,3; Gang Li1,2,3 | |
2023-05-23 | |
Source Publication | BMC Bioinformatics |
ISSN | 1471-2105 |
Volume | 24Issue:1Pages:214 |
Abstract | Background: A variety of high-throughput analyses, such as transcriptome, proteome, and metabolome analysis, have been developed, producing unprecedented amounts of omics data. These studies generate large gene lists, of which the biological significance shall be deeply understood. However, manually interpreting these lists is difficult, especially for non-bioinformatics-savvy scientists. Results: We developed an R package and a corresponding web server—Genekitr, to assist biologists in exploring large gene sets. Genekitr comprises four modules: gene information retrieval, ID (identifier) conversion, enrichment analysis and publication-ready plotting. Currently, the information retrieval module can retrieve information on up to 23 attributes for genes of 317 organisms. The ID conversion module assists in ID-mapping of genes, probes, proteins, and aliases. The enrichment analysis module organizes 315 gene set libraries in different biological contexts by over-representation analysis and gene set enrichment analysis. The plotting module performs customizable and high-quality illustrations that can be used directly in presentations or publications. Conclusions: This web server tool will make bioinformatics more accessible to scientists who might not have programming expertise, allowing them to perform bioinformatics tasks without coding. |
Keyword | Bioinformatics Tool Gene Set Enrichment Analysis Non-programming Bioinformatics Plotting Web Server |
DOI | 10.1186/s12859-023-05342-9 |
URL | View the original |
Indexed By | SCIE |
Language | 英語English |
WOS Research Area | Biochemistry & Molecular Biology ; Biotechnology & Applied Microbiology ; Mathematical & Computational Biology |
WOS Subject | Biochemical Research Methods ; Biotechnology & Applied Microbiology ; Mathematical & Computational Biology |
WOS ID | WOS:000994251800002 |
Publisher | BMCCAMPUS, 4 CRINAN ST, LONDON N1 9XW, ENGLAND |
Scopus ID | 2-s2.0-85159966813 |
Fulltext Access | |
Citation statistics | |
Document Type | Journal article |
Collection | Ministry of Education Frontiers Science Center for Precision Oncology, University of Macau Faculty of Health Sciences Cancer Centre DEPARTMENT OF BIOMEDICAL SCIENCES |
Corresponding Author | Gang Li |
Affiliation | 1.Ministry of Education Frontiers Science Center for Precision Oncology,Faculty of Health Sciences,University of Macau,Macao 2.Cancer Centre,Faculty of Health Sciences,University of Macau,Macao 3.Department of Biomedical Science,Faculty of Health Sciences,University of Macau,Macao |
First Author Affilication | Faculty of Health Sciences; Cancer Centre |
Corresponding Author Affilication | Faculty of Health Sciences; Cancer Centre |
Recommended Citation GB/T 7714 | Yunze Liu,Gang Li. Empowering biologists to decode omics data: the Genekitr R package and web server[J]. BMC Bioinformatics, 2023, 24(1), 214. |
APA | Yunze Liu., & Gang Li (2023). Empowering biologists to decode omics data: the Genekitr R package and web server. BMC Bioinformatics, 24(1), 214. |
MLA | Yunze Liu,et al."Empowering biologists to decode omics data: the Genekitr R package and web server".BMC Bioinformatics 24.1(2023):214. |
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