ShinyArchR.UiO: user-friendly,integrative and open-source tool for visualization of single-cell ATAC-seq data using ArchR

Abstract

Motivation Mapping of chromatin accessibility landscapes in single-cells and the integration with gene expression enables a better understanding of gene regulatory mechanisms defining cell identities and cell-fate determination in development and disease. Generally, raw data generated from single-cell Assay for Transposase-Accessible Chromatin sequencing (scATAC-seq) are deposited in repositories that are generally inaccessible due to lack of in-depth knowledge of computational programming. Results We have developed ShinyArchR.UiO, an R-based shiny app, that facilitates scATAC-seq data accessibility and visualisation in a user-friendly, interactive, and open-source web interface. ShinyArchR.UiO is an application that can streamline collaborative efforts for interpretation of massive chromatin accessibility datasets and allow for open access data sharing for wider audiences. Availability https://Github.com/EskelandLab/ShinyArchRUiO and a demo server with a haematopoietic tutorial dataset https://cancell.medisin.uio.no/ShinyArchR.UiO Supplementary Information Supplementary data are available at Bioinformatics online.

A multi-omics approach to visualize early neuronal differentiation from hESCs in 4D

“…It is generally necessary to have expertise in bioinformatics for the analysis of large single-cell sequence data analysis. Open-access interfaces based on open-source tools enabled us to make our scRNA- and scATAC-seq data available to more people, abiding by the Findability, Accessibility, Interoperability, and Reusability (FAIR) principles ( Ouyang et al., 2021 ; Sharma et al., 2021 ).The users can explore scRNA-seq data in hESCNeuroDiffscRNA and plot high resolution figures of their genes of interest under seven different tabs ( Figures S7 A–S7H; Table S7 ). This includes exploration of 1) Gene expression UMAPS as illustrated for POU5F1 and NTRK1 ; 2) gene co-expression analysis, here shown for PHC1/PHC2 and NEUROG1/NTRK1 ; 3) different gene and cluster expression configurations, such as heatmaps, violin-, box-, proportion- and bubble plots.…”

“…Although numerous studies have used the LSX cocktail for neural induction, to our knowledge this is the first study that has shared all scRNA-seq and scATAC-seq data in such transparent and interactive format. Thus the strength of this study is the high quality data and the presentation of our single-cell data in two visualization tools, ShinyCell and in-house developed ShinyArchR.UiO ( Ouyang et al., 2021 ; Sharma et al., 2021 ), that are openly available for users. These tools allow the users to explore candidate genes and utilize a comprehensive set of functionalities, beyond the analysis presented.…”

A multi-omics approach to visualize early neuronal differentiation in 4D

“…Large dataset analyses, such as single-cell sequence analysis, generally require bioinformatics expertise for interpretation. We have made our scRNA- and scATAC-seq data accessible to a broader audience by providing open access web-interfaces based on open-source tools, abiding by the Findability, Accessibility, Interoperability, and Reusability (FAIR) principles (Ouyang et al, 2021; Sharma et al, 2021). The users can explore scRNA-seq data in hESCNeuroDiffscRNA and plot high resolution figures of their genes of interest under seven different tabs ( Fig S7A-H ).…”

“…Although numerous studies have used the LSX cocktail for neural induction, to our knowledge this is the first study that has shared all scRNA data in such transparent and interactive format. Thus, a strength of this study is the presentation of our single-cell data in two visualization tools, ShinyCell and inhouse developed ShinyArchR.UiO (Ouyang et al, 2021; Sharma et al, 2021), that are openly available for users. These tools allow the users to explore candidate genes and utilize a comprehensive set of functionalities, beyond the fate specification analysis presented here.…”

Multi-omics approach reveals dysregulated genes during hESCs neuronal differentiation exposure to paracetamol

“…Abiding by the Findability, Accessibility, Interoperability, and Reusability (FAIR) principles, we further provide full access to the scRNA-seq and scATAC-seq datasets. These datasets can be visualized in the open access shiny web platforms for scRNA-seq ( hescneuroparacet ) and integrative scATAC-seq/scRNA-seq ( hescneurodiffparacet ) (101,102). Moreover, these webtools also allow for data correlation with other published gene expression datasets, and enable plotting, exporting and downloading high resolution figures of one’s genes of interest as gene expression and gene co-expression analysis UMAPs of any gene.…”