Single cell sequencing

Unparalleled perspective on the biology of single cells

Single-cell Gene-expression analysis has been chosen by SCIENCE editors as “Breakthrough of the Year 2018”. Now, this technique has become available for any researcher to study the processes behind cellular development and disease.

Standard RNA-seq measures average gene-expression levels, which is inadequate for heterogenous samples. Single cell sequencing does not require sorting your cells into small populations based on known markers. It allows you to administer any cell population – as a whole or pre-sorted – and create gene-expression profiles on each cell individually. Unsupervised clustering algorithms then visualize your cells in plots, placing cells with similar expression profiles together. You can clearly discern between cell types and study the heterogeneity within those clusters. Visualizing cell-to-cell variability has never been more attainable.

Mask Group 38 Service page Single Cell sequencing

Benefits of Single cell sequencing:

Rare cell populations 01 Service page Single Cell sequencing

Investigate rare cell populations such as stem cells, primary cells or cells refractory to treatment

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Cell regulation 01 Service page Single Cell sequencing

Monitor cellular regulation and differentiation processes

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Drug response 01 Service page Single Cell sequencing

Observe drug responses within cell populations and/or over time

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New biomarkers 01 Service page Single Cell sequencing

Discover new biomarkers

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A group of people with the appropriate skills work with you on your project:

Getting started 1 01 Service page Single Cell sequencing

Single cell sequencing poses unique challenges since it requires freshly dissociated, viable cell suspensions.

Having in-house expertise in cell-handling as well as NGS sample preparation, is crucial. Equally important is the guidance before the start of your project. A PhD-level project manager will give expert advice and collaborates with you to optimize the workflow for your specific cell culture, tissue or organ. GenomeScan has set up a streamlined workflow and logistics strategy to optimally preserve the biological relevance.

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Methodology 2 01 Service page Single Cell sequencing

GenomeScan has selected the Chromium instrument of 10X Genomics as the most reproducible and cost-effective method for data-generation.

Individual cells are loaded into Gel Bead-In EMulsions droplets (GEMs) to uniquely barcode 500 to 50.000 cells per sample.

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Ready for interpretation 3 01 Service page Single Cell sequencing

Your single cell gene-expression data is directly accessible for interpretation in an interactive visualization tool: the Chromium Loupe browser.

The raw RNA-seq output is processed by our high capacity servers by the Cell Ranger analysis pipeline. This generates all files for further analysis, that you can directly read from the Hard Disk that you receive. In the Loupe browser, you can further explore gene expression differences by creating groups, using t-SNE cluster plots and gene-expression tables.

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Detailed data analysis 4 01 Service page Single Cell sequencing

For comparative analysis such as time-series or drug treatments, additional data-analysis is required.

Our experienced bioinformaticians have adapted analysis methods to identify common sources of variation between datasets and to perform correction, so that statistically relevant data is reported.

You receive a detailed report of the transcriptomic changes between cell-clusters and samples, including leading to the fastest way to answering your research question. Alternatively, we can provide expert guidance for BioIT specialists that have experience in data-analysis using R-packages.