Single-cell RNA Sequencing

scRNA-seq

Assessing gene expression in single cells is critical to better understand cellular behaviors and compositions in developing, adult and pathological tissues. Recent technical advances have enabled RNA sequencing in single cells, which led to insights into dynamics of differentiation, cellular responses and the stochastic nature of transcription.

Challenges

The need for reverse transcription and high amplification of very small amounts of RNA found in an individual cell renders single-cell transcriptomics prone to loss and bias. Relevant signals, like cell identity, that are needed to reliably group cells based on their type, are confounded by technical noise and sparsity of the readout. Stochastic molecular processes drive transcription in discrete bursts, occuring as seemingly random fluctuations in gene expression that may range from not expressed, to low, to high in a given cell.

Low input for a high number of cells
Sparsity / Zero-inflation of expression values
Cell-to-Cell heterogeneity

Pipeline

Results

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