8/4/2023 0 Comments Cluego cytoscape tutorial![]() Soon after, it was clear that Galaxy offered more than simplicity, and quickly became one of the best platforms to guarantee the transparency and reproducibility of full computational analyses for biologists and bioinformaticians ( 9). 2 The original Galaxy server offered data search and manipulation options, multiple bioinformatics tools, and the possibility of easily combining different analyses thanks to an element called the “History” which allowed the storage of every intermediate result ( 8). It was originally built as a platform for researchers without programming experience and started as a public server with an emphasis on simplicity. Galaxy is one of the most popular multi-purpose bioinformatics platforms. The code is open source and can be reviewed or cloned from. GSA Central’s website was built as a GitHub website 1 using HTML, CSS, and javascript. Here we introduce “GSA Central,” a web platform to perform, learn, and discuss GSA, which is divided into five sections ( Figure 1): (i) “Galaxy-GSA” (a collection of a variety of GSA tools inside a Galaxy environment), (ii) “GSA Classroom” (a database of online GSA courses and videos), (iii) “GSARefDB” (a comprehensive database of all published GSA papers), (iv) “GSA BenchmarKING” (a repository of tools to benchmark GSA methods and software), and (v) “GSA Blog” (a place to discuss novel GSA-related topics). In this platform, biomedical researchers can use simplified versions of the existing tools, find information about all existing methods and reviews, discuss new developments, follow online lessons, and more. In this context, our goal is to create a web platform that can serve as a focal point for GSA practitioners, both novice and experts. Multiple reviews have been written and multiple courses have been offered, and, consequently, a GSA sub-field with its own jargon, methods, tools, and opposing schools has appeared. Therefore, numerous independent tools have been created to perform GSA on different types of datasets or from different programming environments, such as GSEA ( 2), DAVID ( 3), Enrichr ( 4), clusterProfiler ( 5), GOseq ( 6), and ClueGO ( 7). GSA has become one of the standard analyses of current omics data analysis workflows. If the query set is made of genes differentially expressed between two experimental conditions, a GSA result can be understood as the gene sets, ontology terms, or pathways significantly enriched between those experimental conditions ( 1). In other words, a statistical method to interpret a query gene set in terms of biological pathways or functionally related gene sets from a reference database ( 1). It has been defined as the statistical comparison of a query gene set to a database of annotated gene sets to transform gene-level experimental results into gene-set-level experimental results. “Gene Set Analysis” (GSA) is an annotation-based approach for omics data analysis. Moreover, we expect this kind of platform to become an example of a “thematic platform” containing all the resources that people in the field might need, an approach that could be extended to other bioinformatics topics or scientific fields. We expect that “GSA Central” will become a useful resource for users looking for introductory learning, state-of-the-art updates, method/tool selection guidelines and insights, tool usage, tool integration under a Galaxy environment, tool design, and tool validation/benchmarking. “GSA Central” contains five different resources: A Galaxy instance containing GSA tools (“Galaxy-GSA”), a portal to educational material (“GSA Classroom”), a comprehensive database of articles (“GSARefDB”), a set of benchmarking tools (“GSA BenchmarKING”), and a blog (“GSA Blog”). In this paper, we introduce a web platform called “GSA Central” which, as its name indicates, acts as a focal point to centralize GSA information and tools useful to beginners, average users, and experts in the GSA field. However, as the field grows, it is becoming more difficult to obtain a clear view of all available methods, resources, and their quality. Hundreds of GSA-related papers have been published, giving birth to a GSA field in Bioinformatics studies. Gene Set Analysis (GSA) is one of the most commonly used strategies to analyze omics data. 2School of Biomedical Engineering, Guangzhou Medical University, Guangzhou, China.1Joint School of Life Sciences, Guangzhou Medical University and Guangzhou Institutes of Biomedicine and Health (Chinese Academy of Sciences), Guangzhou, China.Xiaowei Huang 1†, Xuanyi Lu 1†, Chengshu Xie 1†, Shaurya Jauhari 1, Zihong Xie 1, Songqing Mei 2 and Antonio Mora 1*
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