QC metrics from CPTAC raw LC-MS/MS data interpreted through multivariate statistics.

ABSTRACT: Shotgun proteomics experiments integrate a complex sequence of processes, any of which can introduce variability. Quality metrics computed from LC-MS/MS data have relied upon identifying MS/MS scans, but a new mode for the QuaMeter software produces metrics that are independent of identifications. Rather than evaluating each metric independently, we have created a robust multivariate statistical toolkit that accommodates the correlation structure of these metrics and allows for hierarchical relationships among data sets. The framework enables visualization and structural assessment of variability. Study 1 for the Clinical Proteomics Technology Assessment for Cancer (CPTAC), which analyzed three replicates of two common samples at each of two time points among 23 mass spectrometers in nine

SUBMITTER: Wang X 

PROVIDER: S-EPMC3982976 | biostudies-literature | 2014 Mar

REPOSITORIES: biostudies-literature