MULTIPLEXED GENE EXPRESSION WITH NANOSTRING TECHNOLOGY
Precisely quantify up to 800 genes in a single sample
Simply send us your samples, and we’ll return a detailed gene expression report in less than two weeks
Multiplex up to 800 targets in a single sample
Compatible with multiple sample types:
Ability to analyse RNA extracted from FFPE tissues
Total or fragmented RNA
Cell lysates
PBMC
Whole blood and plasma
Urine and saliva
CSF and synovial fluid
Produce robust data from low amounts of input sample
Pre-designed gene panels or create your own custom panel
3D biology: analyse DNA, RNA and protein in a single sample - read more+
Digital spatial profiling: understand tumour and microenvironment with morphological context whilst maintaining sample integrity - read more+
READY-TO-USE GENE EXPRESSION PANELS
Choose from NanoString’s broad portfolio of expertly curated, ready-to-use gene expression panels.
Each multiplex panel contains up to 770 genes and is customisable for up to 30 additional unique targets.
For more details on ready-to-use panels click here+

FAST AND EFFICIENT WORKFLOW
Placing an order couldn’t be easier - simply complete our enquiry form and a member of our team will respond with a study proposal.
Unsure which panel is right for your study? Contact us and one of our team will be in touch to discuss your requirements and advise the most appropriate study design. To see a complete list of available ready-to-use panels, click here

GENERATING DATA FROM ARCHIVAL FFPE SAMPLES
Formalin-Fixed Paraffin-Embedded samples are notoriously difficult for molecular analysis
with high variability, low yield, and in many cases, high degradation.
The NanoString nCounter analysis system eliminates these challenges by utilising molecular “barcodes” and single molecule imaging to directly hybridise and detect hundreds of unique transcripts in a single reaction without any amplification steps that might introduce bias.
With a single curl of FFPE material, nCounter generates data correlating with that generated from matched fresh frozen material.
Correlation between FFPE and fresh-frozen: NanoString and qPCR
Independent research by Reis PP, et al., “mRNA Transcript Quantification in Archival Samples
Using Multiplexed, Color-coded Probes” evaluates the results of FFPE analysis performed on the nCounter system compared to qPCR.
The figure on the left shows nCounter data which has a correlation coefficient between FFPE and fresh-frozen of 0.90, and the figure on the right shows equivalent data for qPCR with a correlation coefficient of 0.50. This illustrates the superiority of nCounter data to that of qPCR for gene expression analysis of FFPE samples.

HOW Nanostring technology works
Nanostring technology is based on direct molecular barcoding of target molecules utilising a unique probe for each target of interest followed by digital detection of each individual target. The target probe consists of 6 colour coded positions with up to 4 colours allowing a diverse range of unique patterns, each relating to a single target ID.
Accurate
Reproducible
Reliable

Up to 770 different target probes can be included with the sample in each well creating a highly multiplexed approach. The individual targets are digitally resolved by the Nanostring nCounter instrument and software during data collection.
Step 1 - Hybridize
Each sample is exposed to a reaction mixture with excess target probes to ensure each target finds a probe pair.
The sample will undergo hybridisation before excess probes are washed off in a two-step magnetic bead-based purification process.

Step 2 - Count
Sample cartridges are scanned by epifluorescence microscopy. CCD capture technology provides a large number of individual target molecule counts.

Step 3 - Data Analysis
The nSolver Analysis Software is used to interrogate the hundreds of thousands of target molecule counts to provide measurements with a high level of precision and accuracy.

Step 4 - Data Output
Visualise data to make inferences about data sets and evaluate gene expression
Along with a raw data file and normalised data, statistical outputs and a variety of publication-quality figures can be produced to add further insights and visualise important data sets.

Heat Maps – identify relationships between all datasets and evaluate gene expression profiles

Violin plots – similar to a box plot by displaying the range of data. They show density of values in a similar way to a histogram and can be used to illustrate relative gene expression in different cell populations

Box plots – these non-parametric analyses display differences between subsets of an experiment, showing the range of data

Scatter plots – compare variables in raw, normalized, grouped or ratio data by using Cartesian coordinates. Identify the trends in the relationship between two variables without data manipulation

Histograms – Display and estimate the probability distribution of a continuous variable
The raw data files are compatible with most 3rd party analysis software, allowing the flexibility for sponsors to perform their own bioinformatics.