Basic Data Analysis
In the search of a state of the art biostatistical analysis of your gene or protein expression data? Look no further.
We offer a complete analysis of your data with state of the art biostatistical methods with full transparency. Each step chosen throughout the data analysis is well described. It also includes a report summarizing the results, tables of the data before and after each analytic step. You also get useful figures in vector-format, designed to be ready for publicizing.
The analysis includes:
- Data filtration
- Detection of unique identification
- Data transformation and normalization test
- Outlier estimation
- Statistical testing
- Data visualization.
Machine learning is utilized to find outliers, adjust p-value in case of low sample size, cluster analysis, and more. Clustering is used to personalized medicine-inspired expanded regulation analysis (if interesting subgroups or sub-studies are implied by clustering, we will do statistical analysis on these).