Cell type identification

Identify and classify
cell types

Single-cell RNA sequencing enables the profiling of gene expression at the single-cell level, allowing for cell type identification and classification based on their unique transcriptional profiles.

Cell Type Identification applications of single-cell sequencing at Single Cell Discoveries
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Applications

Classifying cells is crucial to get a detailed understanding of how tissues function and to reveal mechanisms underlying pathological states.
Transcriptional profiling plus differential gene expression analysis helps find markers for specific cell types or subpopulations, provides insight into the role of heterogeneity in disease, and reveals how particular environments can impact tumor biology.

Identify new and rare cell (sub)types

Cell type identification with single-cell sequencing involves the partitioning of data into clusters of individual cells, where each cluster is defined by a similar gene expression signature that distinguishes it from the cells in other clusters. This enables the identification of rare or previously unknown cell (sub)types that would be missed in traditional bulk RNA sequencing experiments. This knowledge is valuable in understanding the heterogeneity of tissues and how this relates to health and disease.

Identification of molecular markers

Identification of transcriptional markers for specific cell types or subpopulations is possible with single cell sequencing. These markers can be used to diagnose pathologies, track the progression of disease, monitor treatment response, and identify potential therapeutic targets.

How we do it

Find cell types in your data

Cell type identification using single-cell RNA sequencing involves clustering cells into groups, where each group has a distinct gene expression signature that differentiates it from other clusters. Using differential gene expression and gene set enrichment analysis, the transcriptome of all cells within a given cluster can be used to identify a specific cell type.

Once these transcriptome profiles are established, it is important to validate new targets that are predicted by the data with another experimental method. Likewise, it is important to determine whether they represent a stable cell type or a transient molecular state.

While this can be partially solved computationally, validation experiments are often crucial to this process. Therefore, it is important to think about follow-up experiments that can confirm the results obtained with single-cell RNA sequencing.

Preliminary or custom data analysis

As part of our project delivery, we provide a preliminary data analysis to jumpstart your analysis. Our experienced bioinformaticians perform this analysis using our custom pipelines, and provide you with an interactive report, raw files, and a brief summary of your data. Additionally, if you require additional support or wish to fully outsource your data analysis, our bioinformatics team can assist you with a custom project, for example: clustering analysis, gene set enrichment analysis, data set integration, and figures ready for publication or internal presentations.

 

Recent case studies

Pioneering 10x Flex on OCT-Embedded Patient Brain Tissue

10x Genomics opened the gates for single-cell sequencing on non-fresh, non-thawed tissue with their Chromium Single Cell Gene Expression Flex (10x Flex) kit. Now, we have been successful in performing…

10x
Neuroscience
Neuroscience
RNA Flex

Publications

Information Guide

Discover our single-cell sequencing solutions

Download our information guide to access an overview of Single Cell Discoveries, explore our single-cell sequencing services, learn how to get started, and gain more valuable insights.