Phantasus, a web application for visual and interactive gene expression analysis

Transcriptomic profiling became a standard approach to quantify a cell state, which led to the accumulation of huge amount of public gene expression datasets. However, both reuse of these datasets or analysis of newly generated ones requires significant technical expertise. Here, we present Phantasu...

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Vydané v:eLife Ročník 13
Hlavní autori: Kleverov, Maksim, Zenkova, Daria, Kamenev, Vladislav, Sablina, Margarita, Artyomov, Maxim N, Sergushichev, Alexey A
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: England eLife Sciences Publications Ltd 03.06.2024
eLife Sciences Publications, Ltd
Predmet:
Annotations
Computational and Systems Biology
Computational Biology - methods
Datasets
Gene expression
Gene Expression Profiling - methods
Humans
interactive analysis
Internet
JavaScript
public data
Quality control
reanalysis
Software
Tools and Resources
Transcriptomics
visualization
computational biology
systems biology
public data
visualization
interactive analysis
none
reanalysis
gene expression
ISSN:2050-084X, 2050-084X
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Popis
Shrnutí:Transcriptomic profiling became a standard approach to quantify a cell state, which led to the accumulation of huge amount of public gene expression datasets. However, both reuse of these datasets or analysis of newly generated ones requires significant technical expertise. Here, we present Phantasus: a user-friendly web application for interactive gene expression analysis which provides a streamlined access to more than 96,000 public gene expression datasets, as well as allows analysis of user-uploaded datasets. Phantasus integrates an intuitive and highly interactive JavaScript-based heatmap interface with an ability to run sophisticated R-based analysis methods. Overall Phantasus allows users to go all the way from loading, normalizing, and filtering data to doing differential gene expression and downstream analysis. Phantasus can be accessed online at https://alserglab.wustl.edu/phantasus or can be installed locally from Bioconductor ( https://bioconductor.org/packages/phantasus ). Phantasus source code is available at https://github.com/ctlab/phantasus under an MIT license.
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These authors contributed equally to this work.
ISSN:2050-084X
2050-084X
DOI:10.7554/eLife.85722