Paper Info
Title
SCANNER: a web platform for annotation, visualization and sharing of single cell RNA-seq data
Abstract
In recent years, efficient scRNA-seq methods have been developed, enabling the transcriptome profiling of single cells massively in parallel. Meanwhile, its high dimensionality and complexity bring challenges to the data analysis and require extensive collaborations between biologists and bioinformaticians and/or biostatisticians. The communication between these two units demands a platform for easy data sharing and exploration. Here we developed Single-Cell Transcriptomics Annotated Viewer (SCANNER), as a public web resource for the scientific community, for sharing and analyzing scRNA-seq data in a collaborative manner. It is easy-to-use without requiring special software or extensive coding skills. Moreover, it equipped a real-time database for secure data management and enables an efficient investigation of the activation of gene sets on a single-cell basis. Currently, SCANNER hosts a database of 19 types of cancers and COVID-19, as well as healthy samples from lungs of smokers and non-smokers, human brain cells and peripheral blood mononuclear cells (PBMC). The database will be frequently updated with datasets from new studies. Using SCANNER, we identified a larger proportion of cancer-associated fibroblasts cells and more active fibroblast growth-related genes in melanoma tissues in female patients compared to male patients. Moreover, we found ACE2 is mainly expressed in lung pneumocytes, secretory cells and ciliated cells and differentially expressed in lungs of smokers and never smokers.
Year
DOI
Venue
2022
10.1093/database/baab086
DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION
DocType
Volume
Issue
Journal
2022
2022
ISSN
Citations 
PageRank 
1758-0463
0
0.34
References 
Authors
0
5
Name
Order
Citations
PageRank
Guoshuai Cai100.68
Xuanxuan Yu200.34
Choonhan Youn300.34
Jun Zhou400.34
Feifei Xiao500.68