ColorCells

ColorCells enables comparative analysis of long noncoding RNAs (lncRNAs) in single-cell RNA sequencing (scRNA-Seq) datasets across six species to identify cell-specific lncRNA expression and variability.

Key Features:

• Large cross-species dataset: Aggregates 167,913 publicly available scRNA-Seq datasets from six species for comparative lncRNA analysis.
• Cell-specific lncRNA identification: Identifies lncRNAs that show notable expression variability across cellular clusters at single-cell resolution.
• Classification performance: Reports that identified lncRNAs exhibit classification abilities comparable to established marker genes.
• Co-expression analysis: Analyzes co-expression between lncRNAs and mRNAs within the same cell clusters to infer potential functional relationships.
• Single-cell focus: Operates on scRNA-Seq data to resolve lncRNA expression patterns at the single-cell level.
• Experimental validation: Includes in vitro experimental validation of lncRNA presence and functions reported from the analyses.

Scientific Applications:

• Marker discovery: Identification of novel lncRNA marker genes for single-cell studies.
• Functional inference: Inferring potential functions of lncRNAs via co-expression with mRNAs.
• Cell-type classification: Using lncRNA expression profiles to classify cell types at single-cell resolution.
• Comparative genomics: Comparative analysis of lncRNA expression patterns across six species.
• Gene regulation and heterogeneity studies: Investigating cellular heterogeneity and gene regulation mechanisms involving lncRNAs.

Methodology:

Performs comparative analysis of lncRNA expression across aggregated scRNA-Seq datasets, identifies cell-specific lncRNAs based on expression variability across cellular clusters, and conducts co-expression analysis between lncRNAs and mRNAs.