Phantasus, a web-application for visual and interactive gene expression analysis
- ITMO University, Russian Federation
- Washington University in St. Louis, United States
Abstract
Transcriptomic profiling became a standard approach to quantify a cell state, which led to 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 96000 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 on-line 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 MIT license.
Data availability
The current manuscript is a computational study, so no data have been generated for this manuscript. The application source code is available at https://github.com/ctlab/phantasus under MIT licence.
-
NRROS negatively regulates ROS in phagocytes during host defense and autoimmunityNCBI Gene Expression Omnibus, GSE53986.
-
The helix-loop-helix protein ID2 governs NK cell fate by tuning their sensitivity to interleukin-15NCBI Gene Expression Omnibus, GSE76466.
-
ILC1 lineage identity is determined by a cis-regulatory element marked by a novel lncRNANCBI Gene Expression Omnibus, GSE101459.
Article and author information
Author details
Alexey A Sergushichev
Funding
Ministry of Science and Higher Education of the Russian Federation (Priority 2030 Federal Academic Leadership Program)
- Maksim Kleverov
- Alexey A Sergushichev
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Marisa Nicolás, Laboratório Nacional de Computação Científica, Brazil
Version history
- Preprint posted: December 12, 2022 (view preprint)
- Received: December 21, 2022
- Accepted: May 13, 2024
- Accepted Manuscript published: May 14, 2024 (version 1)
- Version of Record published: June 3, 2024 (version 2)
Copyright
© 2024, Kleverov et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 1,215
- views
-
- 153
- downloads
-
- 1
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
A two-part list of links to download the article, or parts of the article, in various formats.
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Phantasus, a web-application for visual and interactive gene expression analysis
eLife 13:e85722.
https://doi.org/10.7554/eLife.85722
Further reading
-
- Computational and Systems Biology
- Neuroscience
How is the information-processing architecture of the human brain organised, and how does its organisation support consciousness? Here, we combine network science and a rigorous information-theoretic notion of synergy to delineate a ‘synergistic global workspace’, comprising gateway regions that gather synergistic information from specialised modules across the human brain. This information is then integrated within the workspace and widely distributed via broadcaster regions. Through functional MRI analysis, we show that gateway regions of the synergistic workspace correspond to the human brain’s default mode network, whereas broadcasters coincide with the executive control network. We find that loss of consciousness due to general anaesthesia or disorders of consciousness corresponds to diminished ability of the synergistic workspace to integrate information, which is restored upon recovery. Thus, loss of consciousness coincides with a breakdown of information integration within the synergistic workspace of the human brain. This work contributes to conceptual and empirical reconciliation between two prominent scientific theories of consciousness, the Global Neuronal Workspace and Integrated Information Theory, while also advancing our understanding of how the human brain supports consciousness through the synergistic integration of information.
-
- Computational and Systems Biology
- Genetics and Genomics
Runs-of-homozygosity (ROH) segments, contiguous homozygous regions in a genome were traditionally linked to families and inbred populations. However, a growing literature suggests that ROHs are ubiquitous in outbred populations. Still, most existing genetic studies of ROH in populations are limited to aggregated ROH content across the genome, which does not offer the resolution for mapping causal loci. This limitation is mainly due to a lack of methods for the efficient identification of shared ROH diplotypes. Here, we present a new method, ROH-DICE (runs-of-homozygous diplotype cluster enumerator), to find large ROH diplotype clusters, sufficiently long ROHs shared by a sufficient number of individuals, in large cohorts. ROH-DICE identified over 1 million ROH diplotypes that span over 100 single nucleotide polymorphisms (SNPs) and are shared by more than 100 UK Biobank participants. Moreover, we found significant associations of clustered ROH diplotypes across the genome with various self-reported diseases, with the strongest associations found between the extended human leukocyte antigen (HLA) region and autoimmune disorders. We found an association between a diplotype covering the homeostatic iron regulator (HFE) gene and hemochromatosis, even though the well-known causal SNP was not directly genotyped or imputed. Using a genome-wide scan, we identified a putative association between carriers of an ROH diplotype in chromosome 4 and an increase in mortality among COVID-19 patients (p-value = 1.82 × 10−11). In summary, our ROH-DICE method, by calling out large ROH diplotypes in a large outbred population, enables further population genetics into the demographic history of large populations. More importantly, our method enables a new genome-wide mapping approach for finding disease-causing loci with multi-marker recessive effects at a population scale.
