Cell type-specific weighting-factors to solve solid organs-specific limitations of single cell RNA-sequencing
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1099284 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR28637106.fastq.gz | Fastqsanger.gz | |||
| SRR28637107.fastq.gz | Fastqsanger.gz | |||
| SRR28637108.fastq.gz | Fastqsanger.gz | |||
| SRR28637109.fastq.gz | Fastqsanger.gz | |||
| SRR28637110.fastq.gz | Fastqsanger.gz |
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Project description:While single-cell RNA-sequencing (scRNA-seq) is a popular method to analyze gene expression and cellular composition at single-cell resolution, it harbors shortcomings: The failure to account for cell-to-cell variations of transcriptome-size (i.e., the total number of transcripts per cell) and also cell dissociation/processing-induced cryptic gene expression. This is particularly a problem when analyzing highly heterogeneous solid tissues/organs, which requires cell dissociation for the analysis. As a result, there exists a discrepancy between bulk RNA-seq result and virtually reconstituted bulk RNA-seq result using its composite scRNA-seq data. To fix this problem, we propose a computationally calculated coefficient, "cell type-specific weighting-factor (cWF)". Here, we introduce a concept and a method of its computation and report cWFs for 76 cell-types across 10 solid organs. Their fidelity is validated by more accurate reconstitution and deconvolution of bulk RNA-seq data of diverse solid organs using the scRNA-seq data and the cWFs of their composite cells. Furthermore, we also show that cWFs effectively predict aging-progression, implicating their diagnostic applications and also their association with aging mechanism. Our study provides an important method to solve critical limitations of scRNA-seq analysis of complex solid tissues/organs. Furthermore, our findings suggest a diagnostic utility and biological significance of cWFs.
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