eVITTA: a web-based visualization and inference toolbox for transcriptome analysis
| Autor: | Jiahe Wang, Yongxing Liu, Junran Yan, Xuanjin Cheng, Stefan Taubert |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
S-Adenosylmethionine
AcademicSubjects/SCI00010 ved/biology.organism_classification_rank.species Inference Computational biology Workflow Transcriptome 03 medical and health sciences 0302 clinical medicine Data visualization Species Specificity Nasopharynx Databases Genetic Genetics Animals Humans Model organism Caenorhabditis elegans 030304 developmental biology 0303 health sciences Internet biology ved/biology business.industry SARS-CoV-2 Data Visualization Gene Expression Profiling COVID-19 biology.organism_classification Immunity Innate Visualization Gene expression profiling Web Server Issue business 030217 neurology & neurosurgery |
| Zdroj: | Nucleic Acids Research |
| ISSN: | 1362-4962 0305-1048 |
| Popis: | Transcriptome profiling is essential for gene regulation studies in development and disease. Current web-based tools enable functional characterization of transcriptome data, but most are restricted to applying gene-list-based methods to single datasets, inefficient in leveraging up-to-date and species-specific information, and limited in their visualization options. Additionally, there is no systematic way to explore data stored in the largest transcriptome repository, NCBI GEO. To fill these gaps, we have developed eVITTA (easy Visualization and Inference Toolbox for Transcriptome Analysis; https://tau.cmmt.ubc.ca/eVITTA/). eVITTA provides modules for analysis and exploration of studies published in NCBI GEO (easyGEO), detailed molecular- and systems-level functional profiling (easyGSEA), and customizable comparisons among experimental groups (easyVizR). We tested eVITTA on transcriptomes of SARS-CoV-2 infected human nasopharyngeal swab samples, and identified a downregulation of olfactory signal transducers, in line with the clinical presentation of anosmia in COVID-19 patients. We also analyzed transcriptomes of Caenorhabditis elegans worms with disrupted S-adenosylmethionine metabolism, confirming activation of innate immune responses and feedback induction of one-carbon cycle genes. Collectively, eVITTA streamlines complex computational workflows into an accessible interface, thus filling the gap of an end-to-end platform capable of capturing both broad and granular changes in human and model organism transcriptomes. Graphical Abstract Graphical AbstractThe eVITTA toolbox provides an integrated graphical workflow to analyze, interpret and compare transcriptome data either extracted from published studies on NCBI GEO, or generated from new profiling experiments. |
| Databáze: | OpenAIRE |
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