Delineation of complex gene expression patterns in single cell RNA-seq data with ICARUS v2.0 Article Swipe

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Andrew Jiang , Linya You , Russell G. Snell , Klaus Lehnert ·

YOU? · · 2023 · Open Access · · DOI: https://doi.org/10.1101/2023.01.23.525100

Complex biological traits and disease often involve patterns of gene expression that can be characterised and examined. Here we present ICARUS v2.0, an update to our single cell RNA-seq analysis web server with additional tools to investigate gene networks and understand core patterns of gene regulation in relation to biological traits. ICARUS v2.0 enables gene co-expression analysis with MEGENA, transcription factor regulated network identification with SCENIC, trajectory analysis with Monocle3, and characterisation of cell-cell communication with CellChat. Cell cluster gene expression profiles may be examined against Genome Wide Association Studies with MAGMA to find significant associations with GWAS traits. Additionally, differentially expressed genes may be compared against the Drug-Gene Interaction database (DGIdb 4.0) to facilitate drug discovery. ICARUS v2.0 offers a comprehensive toolbox of the latest single cell RNA-seq analysis methodologies packed into an efficient, user friendly, tutorial style web server application (accessible at https://launch.icarus-scrnaseq.cloud.edu.au/ ) that enables single cell RNA-seq analysis tailored to the user’s dataset.

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Icarus

Computational Biology

Biology

Gene Expression

Web Server

Gene Regulatory Network

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ICARUS Computational biology Gene Biology Gene expression RNA-Seq Toolbox Web server Gene regulatory network Genetics Transcriptome Computer science World Wide Web The Internet Physics Particle physics Programming language

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Type: preprint
Language: en
Landing Page: https://doi.org/10.1101/2023.01.23.525100
PDF: https://www.biorxiv.org/content/biorxiv/early/2023/01/24/2023.01.23.525100.full.pdf
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Cited By: 3
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DOI: https://doi.org/10.1101/2023.01.23.525100

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Title: Delineation of complex gene expression patterns in single cell RNA-seq data with ICARUS v2.0

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Type: preprint

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Language: en

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Publication year: 2023

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Publication date: 2023-01-24

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Authors: Andrew Jiang, Linya You, Russell G. Snell, Klaus Lehnert

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Landing page: https://doi.org/10.1101/2023.01.23.525100

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PDF URL: https://www.biorxiv.org/content/biorxiv/early/2023/01/24/2023.01.23.525100.full.pdf

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Concepts: ICARUS, Computational biology, Gene, Biology, Gene expression, RNA-Seq, Toolbox, Web server, Gene regulatory network, Genetics, Transcriptome, Computer science, World Wide Web, The Internet, Physics, Particle physics, Programming language

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Cited by: 3

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