PharmVIP: A Web-Based Tool for Pharmacogenomic Variant Analysis and Interpretation.
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ABSTRACT:
SUBMITTER: Piriyapongsa J
PROVIDER: S-EPMC8618518 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:With the continuing rise of lipidomic studies, there is an urgent need for a useful and comprehensive tool to facilitate lipidomic data analysis. The most important features making lipids different from general metabolites are their various characteristics, including their lipid classes, double bonds, chain lengths, etc. Based on these characteristics, lipid species can be classified into different categories and, more interestingly, exert specific biological functions in a group. In an effort to simplify lipidomic analysis workflows and enhance the exploration of lipid characteristics, we have developed a highly flexible and user-friendly web server called LipidSig. It consists of five sections, namely, Profiling, Differential Expression, Correlation, Network and Machine Learning, and evaluates lipid effects on cellular or disease phenotypes. One of the specialties of LipidSig is the conversion between lipid species and characteristics according to a user-defined characteristics table. This function allows for efficient data mining for both individual lipids and subgroups of characteristics. To expand the server's practical utility, we also provide analyses focusing on fatty acid properties and multiple characteristics. In summary, LipidSig is expected to help users identify significant lipid-related features and to advance the field of lipid biology. The LipidSig webserver is freely available at http://chenglab.cmu.edu.tw/lipidsig.
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Project description:We report a web-based tool for analysis of experiments using indirect calorimetry to measure physiological energy balance. CalR simplifies the process to import raw data files, generate plots, and determine the most appropriate statistical tests for interpretation. Analysis using the generalized linear model (which includes ANOVA and ANCOVA) allows for flexibility in interpreting diverse experimental designs, including those of obesity and thermogenesis. Users also may produce standardized output files for an experiment that can be shared and subsequently re-evaluated using CalR. This framework will provide the transparency necessary to enhance consistency, rigor, and reproducibility. The CalR analysis software will greatly increase the speed and efficiency with which metabolic experiments can be organized, analyzed per accepted norms, and reproduced and will likely become a standard tool for the field. CalR is accessible at https://CalRapp.org/.
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Project description:BackgroundA major challenge of high throughput transcriptome studies is presenting the data to researchers in an interpretable format. In many cases, the outputs of such studies are gene lists which are then examined for enriched biological concepts. One approach to help the researcher interpret large gene datasets is to associate genes and informative terms (iTerm) that are obtained from the biomedical literature using the eGIFT text-mining system. However, examining large lists of iTerm and gene pairs is a daunting task.ResultsWe have developed WebGIVI, an interactive web-based visualization tool ( http://raven.anr.udel.edu/webgivi/ ) to explore gene:iTerm pairs. WebGIVI was built via Cytoscape and Data Driven Document JavaScript libraries and can be used to relate genes to iTerms and then visualize gene and iTerm pairs. WebGIVI can accept a gene list that is used to retrieve the gene symbols and corresponding iTerm list. This list can be submitted to visualize the gene iTerm pairs using two distinct methods: a Concept Map or a Cytoscape Network Map. In addition, WebGIVI also supports uploading and visualization of any two-column tab separated data.ConclusionsWebGIVI provides an interactive and integrated network graph of gene and iTerms that allows filtering, sorting, and grouping, which can aid biologists in developing hypothesis based on the input gene lists. In addition, WebGIVI can visualize hundreds of nodes and generate a high-resolution image that is important for most of research publications. The source code can be freely downloaded at https://github.com/sunliang3361/WebGIVI . The WebGIVI tutorial is available at http://raven.anr.udel.edu/webgivi/tutorial.php .
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Project description:BackgroundNext-generation sequencing (NGS) has been widely used in both clinics and research. It has become the most powerful tool for diagnosing genetic disorders and investigating disease etiology through the discovery of genetic variants. Variants identified by NGS are stored in variant call format (VCF) files. However, querying and filtering VCF files are extremely difficult for researchers without programming skills. Furthermore, as the mutation data are increasing exponentially, there is an urgent need to develop tools to manage these variant data in a centralized way.MethodsThe VCF-Server was developed as a web-based visualization tool to support the interactive analysis of genetic variant data. It allows researchers and medical geneticists to manage, annotate, filter, query, and export variants in a fast and effective way.ResultsIn this study, we developed the VCF-Server, a powerful and easily accessible tool for researchers and medical geneticists to perform variant analysis. Users can query VCFs, annotate, and filter variants without knowing programming code. Once the VCF file is uploaded, VCF-Server allows users to annotate the VCF with commonly used databases or user-defined variant annotations (including variant blacklist and whitelist). Variant information in the VCF is shown visually via the interactive graphical interface. Users can filter the variants with flexible filtering rules, and the prioritized variants can be exported locally for further analysis. As VCF-Server adopts a web file system, files in the VCF-Server can be stored and managed in a centralized way. Moreover, VCF-Server allows direct web-based analysis (accessible through either desktop computers or mobile devices) as well as local deployment.ConclusionsWith an easy-to-use graphical interface, VCF-Server allows researchers with little bioinformatics background to explore and mine mutation data, which may broaden the application of NGS technology in clinics and research. The tool is freely available for use at https://www.diseasegps.org/VCF-Server?lan = eng.
| S-EPMC6625089 | biostudies-literature
Project description:BACKGROUND:miRNAs regulate the expression of several genes with one miRNA able to target multiple genes and with one gene able to be simultaneously targeted by more than one miRNA. Therefore, it has become indispensable to shorten the long list of miRNA-target interactions to put in the spotlight in order to gain insight into understanding the regulatory mechanism orchestrated by miRNAs in various cellular processes. A reasonable solution is certainly to prioritize miRNA-target interactions to maximize the effectiveness of the downstream analysis. RESULTS:We propose a new and easy-to-use web tool MIENTURNET (MicroRNA ENrichment TURned NETwork) that receives in input a list of miRNAs or mRNAs and tackles the problem of prioritizing miRNA-target interactions by performing a statistical analysis followed by a fully featured network-based visualization and analysis. The statistics is used to assess the significance of an over-representation of miRNA-target interactions and then MIENTURNET filters based on the statistical significance associated with each miRNA-target interaction. In addition, the holistic approach of the network theory is used to infer possible evidences of miRNA regulation by capturing emergent properties of the miRNA-target regulatory network that would be not evident through a pairwise analysis of the individual components. CONCLUSION:MIENTURNET offers the possibility to consistently perform both statistical and network-based analyses by using only a single tool leading to a more effective prioritization of the miRNA-target interactions. This has the potential to avoid researchers without computational and informatics skills to navigate multiple websites and thus to independently investigate miRNA activity in every cellular process of interest in an easy and at the same time exhaustive way thanks to the intuitive web interface. The web application along with a well-documented and comprehensive user guide are freely available at http://userver.bio.uniroma1.it/apps/mienturnet/ without any login requirement.
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