Mass spectrometry is widely employed for biomarker discovery purposes. Despite of it intense application some problems should be considered to verify the data validity. The main critical aspect are:
- Matrix effect evaluation; matrix effect is related to instrumental signal variation due to the presence of various matrix molecular species (e.g.: urinary and plasma high abundant molecules) that give rise to biomarker signal instability. To check the presence of matrix effect, it is possible to use specific algorithms and data acquisition procedure (e.g.: application of PROSAD method).
- Data extraction; This step makes possible to extract the biomarker expression data, as a table, to be elaborated using dedicated statistical analysis (mainly ANOVA MANOVA). The criticism associated to this step is the high amount of data that must be processed. It is so necessary a high efficient server or the use of high throughput data extraction technology like CUDA (advanced graphical processor parallelization).
- Data alignment; in this phase the different biomarker signals are aligned inter-sample so to compare the biomarker expressions. The alignment should be carefully checked. In fact, often a singular biomarker signal is erroneously attributed to two different one and this leads to artifact.