Asc-Seurat: analytical single-cell Seurat-based web application

Pereira, W. J.; Almeida, F. M.; Conde, D.; Balmant, K. M.; Triozzi, P. M.; Schmidt, H. W.; Dervinis, C.; Pappas, Jr, G. J.; Kirst, M.

doi:10.1186/s12859-021-04472-2

Asc-Seurat: analytical single-cell Seurat-based web application

Journal Article · Thu Nov 18 00:00:00 EST 2021 · BMC Bioinformatics

DOI:https://doi.org/10.1186/s12859-021-04472-2· OSTI ID:1831282

; Almeida, F. M.; Conde, D.; Balmant, K. M.; Triozzi, P. M.; Schmidt, H. W.; Dervinis, C.; Pappas, Jr, G. J.; Kirst, M.

Abstract Background

Single-cell RNA sequencing (scRNA-seq) has revolutionized the study of transcriptomes, arising as a powerful tool for discovering and characterizing cell types and their developmental trajectories. However, scRNA-seq analysis is complex, requiring a continuous, iterative process to refine the data and uncover relevant biological information. A diversity of tools has been developed to address the multiple aspects of scRNA-seq data analysis. However, an easy-to-use web application capable of conducting all critical steps of scRNA-seq data analysis is still lacking.

Summary

We present Asc-Seurat, a feature-rich workbench, providing an user-friendly and easy-to-install web application encapsulating tools for an all-encompassing and fluid scRNA-seq data analysis. Asc-Seurat implements functions from the Seurat package for quality control, clustering, and genes differential expression. In addition, Asc-Seurat provides a pseudotime module containing dozens of models for the trajectory inference and a functional annotation module that allows recovering gene annotation and detecting gene ontology enriched terms. We showcase Asc-Seurat’s capabilities by analyzing a peripheral blood mononuclear cell dataset.

Conclusions

Asc-Seurat is a comprehensive workbench providing an accessible graphical interface for scRNA-seq analysis by biologists. Asc-Seurat significantly reduces the time and effort required to analyze and interpret the information in scRNA-seq datasets.

View Journal Article

Research Organization:: University of Florida, Gainesville, FL (United States)

Sponsoring Organization:: USDOE; USDOE Office of Science (SC), Biological and Environmental Research (BER)

Grant/Contract Number:: SC0018247

OSTI ID:: 1831282

Alternate ID(s):: OSTI ID: 1975671

Journal Information:: BMC Bioinformatics, Journal Name: BMC Bioinformatics Journal Issue: 1 Vol. 22; ISSN 1471-2105

Publisher:: Springer Science + Business MediaCopyright Statement

Country of Publication:: United Kingdom

Language:: English

References (23)

The Comprehensive R Archive Network: The Comprehensive R Archive Network Hornik, Kurt Wiley Interdisciplinary Reviews: Computational Statistics, Vol. 4, Issue 4 https://doi.org/10.1002/wics.1212	journal	May 2012
Comprehensive Integration of Single-Cell Data Stuart, Tim; Butler, Andrew; Hoffman, Paul Cell, Vol. 177, Issue 7 https://doi.org/10.1016/j.cell.2019.05.031	journal	June 2019
A hitchhiker's guide to single-cell transcriptomics and data analysis pipelines Nayak, Richa; Hasija, Yasha Genomics, Vol. 113, Issue 2 https://doi.org/10.1016/j.ygeno.2021.01.007	journal	March 2021
Gene Ontology: tool for the unification of biology Ashburner, Michael; Ball, Catherine A.; Blake, Judith A. Nature Genetics, Vol. 25, Issue 1 https://doi.org/10.1038/75556	journal	May 2000
Multiplexed droplet single-cell RNA-sequencing using natural genetic variation Kang, Hyun Min; Subramaniam, Meena; Targ, Sasha Nature Biotechnology, Vol. 36, Issue 1 https://doi.org/10.1038/nbt.4042	journal	December 2017
Mapping identifiers for the integration of genomic datasets with the R/Bioconductor package biomaRt Durinck, Steffen; Spellman, Paul T.; Birney, Ewan Nature Protocols, Vol. 4, Issue 8 https://doi.org/10.1038/nprot.2009.97	journal	July 2009
Detection and removal of barcode swapping in single-cell RNA-seq data Griffiths, Jonathan A.; Richard, Arianne C.; Bach, Karsten Nature Communications, Vol. 9, Issue 1 https://doi.org/10.1038/s41467-018-05083-x	journal	July 2018
Single-cell trajectories reconstruction, exploration and mapping of omics data with STREAM Chen, Huidong; Albergante, Luca; Hsu, Jonathan Y. Nature Communications, Vol. 10, Issue 1 https://doi.org/10.1038/s41467-019-09670-4	journal	April 2019
RNA sequencing: the teenage years Stark, Rory; Grzelak, Marta; Hadfield, James Nature Reviews Genetics, Vol. 20, Issue 11 https://doi.org/10.1038/s41576-019-0150-2	journal	July 2019
A comparison of single-cell trajectory inference methods Saelens, Wouter; Cannoodt, Robrecht; Todorov, Helena Nature Biotechnology, Vol. 37, Issue 5 https://doi.org/10.1038/s41587-019-0071-9	journal	April 2019
User-friendly, scalable tools and workflows for single-cell RNA-seq analysis Moreno, Pablo; Huang, Ni; Manning, Jonathan R. Nature Methods, Vol. 18, Issue 4 https://doi.org/10.1038/s41592-021-01102-w	journal	March 2021
Tutorial: guidelines for the computational analysis of single-cell RNA sequencing data Andrews, Tallulah S.; Kiselev, Vladimir Yu; McCarthy, Davis Nature Protocols, Vol. 16, Issue 1 https://doi.org/10.1038/s41596-020-00409-w	journal	December 2020
SC1: A Tool for Interactive Web-Based Single-Cell RNA-Seq Data Analysis Moussa, Marmar; Măndoiu, Ion I. Journal of Computational Biology, Vol. 28, Issue 8 https://doi.org/10.1089/cmb.2021.0051	journal	August 2021
alona: a web server for single-cell RNA-seq analysis Franzén, Oscar; Björkegren, Johan L. M. Bioinformatics, Vol. 36, Issue 12 https://doi.org/10.1093/bioinformatics/btaa269	journal	April 2020
ASAP: a web-based platform for the analysis and interactive visualization of single-cell RNA-seq data Gardeux, Vincent; David, Fabrice P. A.; Shajkofci, Adrian Bioinformatics, Vol. 33, Issue 19 https://doi.org/10.1093/bioinformatics/btx337	journal	May 2017
The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2018 update Afgan, Enis; Baker, Dannon; Batut, Bérénice Nucleic Acids Research, Vol. 46, Issue W1 https://doi.org/10.1093/nar/gky379	journal	May 2018
BioMart – biological queries made easy Smedley, Damian; Haider, Syed; Ballester, Benoit BMC Genomics, Vol. 10, Issue 1 https://doi.org/10.1186/1471-2164-10-22	journal	January 2009
PIVOT: platform for interactive analysis and visualization of transcriptomics data Zhu, Qin; Fisher, Stephen A.; Dueck, Hannah BMC Bioinformatics, Vol. 19, Issue 1 https://doi.org/10.1186/s12859-017-1994-0	journal	January 2018
NASQAR: a web-based platform for high-throughput sequencing data analysis and visualization Yousif, Ayman; Drou, Nizar; Rowe, Jillian BMC Bioinformatics, Vol. 21, Issue 1 https://doi.org/10.1186/s12859-020-03577-4	journal	June 2020
EmptyDrops: distinguishing cells from empty droplets in droplet-based single-cell RNA sequencing data Lun, Aaron T. L.; Riesenfeld, Samantha; Andrews, Tallulah Genome Biology, Vol. 20, Issue 1 https://doi.org/10.1186/s13059-019-1662-y	journal	March 2019
Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression Hafemeister, Christoph; Satija, Rahul Genome Biology, Vol. 20, Issue 1 https://doi.org/10.1186/s13059-019-1874-1	journal	December 2019
Current best practices in single‐cell RNA‐seq analysis: a tutorial Luecken, Malte D.; Theis, Fabian J. Molecular Systems Biology, Vol. 15, Issue 6 https://doi.org/10.15252/msb.20188746	journal	June 2019
BingleSeq: a user-friendly R package for bulk and single-cell RNA-Seq data analysis Dimitrov, Daniel; Gu, Quan PeerJ, Vol. 8 https://doi.org/10.7717/peerj.10469	journal	January 2020

Similar Records

ACTINN: automated identification of cell types in single cell RNA sequencing

Journal Article · Mon Jul 29 00:00:00 EDT 2019 · Bioinformatics · OSTI ID:1799618

ACTINN: automated identification of cell types in single cell RNA sequencing

Journal Article · Sun Jul 28 20:00:00 EDT 2019 · Bioinformatics · OSTI ID:1922564

Related Subjects

60 APPLIED LIFE SCIENCES
Gene expression
Single-cell RNA sequencing
Web application
scRNA-seq

Asc-Seurat: analytical single-cell Seurat-based web application

Citation Formats

References (23)

Similar Records

Related Subjects