ColorCells: a database of expression, classification and functions of lncRNAs in single cells.
Ling-Ling ZhengJing-Hua XiongWu-Jian ZhengJun-Hao WangZi-Liang HuangZhi-Rong ChenXin-Yao SunYi-Min ZhengKe-Ren ZhouBin LiShun LiuLiang-Hu QuJian-Hua YangPublished in: Briefings in bioinformatics (2021)
Although long noncoding RNAs (lncRNAs) have significant tissue specificity, their expression and variability in single cells remain unclear. Here, we developed ColorCells (http://rna.sysu.edu.cn/colorcells/), a resource for comparative analysis of lncRNAs expression, classification and functions in single-cell RNA-Seq data. ColorCells was applied to 167 913 publicly available scRNA-Seq datasets from six species, and identified a batch of cell-specific lncRNAs. These lncRNAs show surprising levels of expression variability between different cell clusters, and has the comparable cell classification ability as known marker genes. Cell-specific lncRNAs have been identified and further validated by in vitro experiments. We found that lncRNAs are typically co-expressed with the mRNAs in the same cell cluster, which can be used to uncover lncRNAs' functions. Our study emphasizes the need to uncover lncRNAs in all cell types and shows the power of lncRNAs as novel marker genes at single cell resolution.
Keyphrases
- single cell
- rna seq
- genome wide analysis
- genome wide identification
- network analysis
- poor prognosis
- high throughput
- machine learning
- genome wide
- induced apoptosis
- binding protein
- emergency department
- artificial intelligence
- squamous cell carcinoma
- signaling pathway
- big data
- electronic health record
- bone marrow
- oxidative stress
- endoplasmic reticulum stress
- dna methylation
- pi k akt