We have designed our analyses to provide you with the best tools to interpret and understand your expression data. Each of our analytical products gives you the right arguments for your further research.
We excel at having short delivery times, without compromising on quality or price. For urgent tasks, there is the opportunity of prioritization and quicker delivery.
You have the opportunity to tailor your solution. By default, all of our advanced data analyzes include statistical analysis and bioinformatics.
We address, which genes/protein expressions found significantly regulated can be annotated through a bioinformatic enrichment analysis. The analysis also investigate if genes or proteins have been found in multiple pathways and suggest which have been found connecting the annotated pathways.
Bioinformatic analysis includes:
Bioinformatic enrichment analysis
Cross sample-group bioinfromatic comparison
In this data analysis, we investigate relevant clusters in your data. Supervised and unsupervised clustering methods are applied to find the clusters in your data to identify potential sub-groups or sub-studies. The cluster analysis allows you to address your data on several levels.
Cluster analysis includes:
Investigation of expression regulations and unique features cross clusters
Bioinformatic analysis with cross cluster comparison
Low sample size is a common phenomenon in pilot-studies and experiments for hypothesis generation but can cause the error that results reflect a single sample instead of the whole sample population. We can adjust the p-value, thus counteracting this effect and calculate bias, giving you the tool to adjust your interpretation of your result.
Low sample size data analysis includes:
Resampling with Jackknife
Calculation of single sample bias
Low sample size adjusted p-values
If you have several datasets, you have the opportunity to perform a multiple comparison data analysis. Here we compare the regulated genes/proteins, unique identification, and bioinformatic annotations.
The multiple comparison analysis includes:
Unique and shared identifications
Unique and shared expression regulation patterns
Unique and shared bioinformatics
Report of the comparison
Report of the individual datasets
We offer a complete analysis of your data with state of the art statistical methods with full transparency. Each step chosen throughout the data analysis will be well described. It also includes a report summarizing the results and tables of the data before and after each analytic step.
Statistical data analysis includes: