CancerSEA: a cancer single-cell state atlas
By Huating Yuan, M. Yan, Guanxiong Zhang, Wei David Liu, Chunyu Deng, Gaoming Liao, Liwen Xu, Tao Luo, Haoteng Yan, Zhilin Long and 4 more. Nucleic Acids Res., 2018
837 citations recorded by the source corpus.
Abstract High functional heterogeneity of cancer cells poses a major challenge for cancer research. Single-cell sequencing technology provides an unprecedented opportunity to decipher diverse functional states of cancer cells at single-cell resolution, and cancer scRNA-seq datasets have been largely accumulated. This emphasizes the urgent need to build a dedicated resource to decode the functional states of cancer single cells. Here, we developed CancerSEA (http://biocc.hrbmu.edu.cn/CancerSEA/ or http://202.97.205.69/CancerSEA/), the first dedicated database that aims to comprehensively explore distinct functional states of cancer cells at the single-cell level. CancerSEA portrays a cancer single-cell functional state atlas, involving 14 functional states (including stemness, invasion, metastasis, proliferation, EMT, angiogenesis, apoptosis, cell cycle, differentiation, DNA damage, DNA repair, hypoxia, inflammation and quiescence) of 41 900 cancer single cells from 25 cancer types. It allows querying which functional states are associated with the gene (or gene list) of interest in different cancers. CancerSEA also provides functional state-associated PCG/lncRNA repertoires across all cancers, in specific cancers, and in individual cancer single-cell datasets. In summary, CancerSEA provides a user-friendly interface for comprehensively searching, browsing, visualizing and downloading functional state activity profiles of tens of thousands of cancer single cells and the corresponding PCGs/lncRNAs expression profiles.
Subfields: Biophysics, Cancer Research, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/294dcc4e1a79ad7c25a5ecb4a3f581b25229b53c
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In Biophysics
Citations in the corpus
- TISCH2: expanded datasets and new tools for single-cell transcriptome analyses of the tumor microenvironment (2022, background): “Although there are several existing scRNA-seq databases that try to collect and display the tumor scRNA-seq datasets, including CancerSCEM (11), DISCO (12) and CancerSEA (13), most of them are limited in the number of datasets included and the coverage of covered cancer types, and have few downstrea”
- TISCH: a comprehensive web resource enabling interactive single-cell transcriptome visualization of tumor microenvironment (2020, background): “CancerSEA (9) explores the functional heterogeneity of only 41 900 cancer cells, and SCPortalen (11) only has 67 146 cells combining human and mouse datasets.”
- CellMarker 2.0: an updated database of manually curated cell markers in human/mouse and web tools based on scRNA-seq data (2022, background): “In recent, some databases manually recruit marker genes for different cell types from available literature information, such as PanglaoDB (18), PCMDB (19) and CancerSEA (20).”