Chromatographic alignment combined with chemometrics profile reconstruction approaches applied to LC-MS data.
This paper presents a full proteomics analysis LC-MS (Liquid Chromatography-Mass Spectrometry) chain combining bio, nano and information technologies in order to quantify targeted proteins in blood sample. The objective is to enable an early detection of pancreatic cancer. We focus on the data processing step which estimates the proteins' concentration. First, we pre-process the data in order to correct time shift between the experiments. We propose to use block matching algorithm. Second, quantification of protein is performed using chemometrics approaches and more precisely CLS, PLS, N-PLS and PARAFAC algorithms. Performances of the various methods have been compared on cytochrome c protein LC-MS analyses.
Paulus
C
C
CEA-LETI, MINATEC, Département des microTechnologies pour la Biologie et la Santé, CEA-Grenoble, 17 Rue des Martyrs, 38054 Grenoble Cedex 9, France.
Bonnet
S
S
Gerfault
L
L
Mery
E
E
Strubel
G
G
Ricoul
F
F
Grangeat
P
P
D000465:Algorithms; D015415:Biomarkers / Q000097:blood; D001774:Blood Chemical Analysis / Q000379:methods*; D001798:Blood Proteins / Q000032:analysis*; D002853:Chromatography, Liquid / Q000379:methods*; D020650:Combinatorial Chemistry Techniques / Q000379:methods*; D013058:Mass Spectrometry / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
D015415:Biomarkers; D001798:Blood Proteins