Bioinformatics

febit’s bioinformatics service for statistics and biomarker signature development

Select from febit’s bioinformatics packages for data analysis, biostatistics and the development of disease-specific signatures:

Gold package including

• Correlation analysis
• Scatter Plots
• Cluster Analysis
• Principal component analysis
• Pair wise comparisons with up to 6 measures
• MA plots

Platinum package additionally including

• Target analysis
• Pathway analysis
• Alignment analysis
• Along chromosome plots

Signature & Classification service

Custom requests

Biomarkers that have been identified by miRNA Biochip experiments, and that have optionally been validated using qRT-PCR, are subject to biostatistical analysis.

It has been shown that miRNA expression patterns, rather than single miRNAs, can serve as biomarker signatures for the detection of human diseases and accurate classification of patient groups. Predictive or diagnostic biomarker signatures, based on the minimum number of significantly deregulated miRNAs that are necessary to distinguish patients from controls, are generated and allow for accurate classification of the investigated patient groups.

Biomarker signatures in clinical research

Regarding complex and diverse diseases such as cancer, a single biomarker will tend to have low specificity since it might not detect the specific disease but rather a more general process; like tumorigenesis in general, and not an organ-specific tumor.

Maintaining high specificity (low false-positive rates) is a very high priority for screenings. Even a small false-positive rate translates into a large number of patients subjected to unnecessary, costly diagnostic procedures and psychological stress. Thus, biomarkers need to be highly specific for a given disease. For a screening program that is both sensitive and specific, the use of biomarker signatures consisting of robust marker sets is a must.