From Centroided to Profile Mode: Machine Learning for Prediction of Peak Width in HRMS Data.

ABSTRACT: Centroiding is one of the major approaches used for size reduction of the data generated by high-resolution mass spectrometry. During centroiding, performed either during acquisition or as a pre-processing step, the mass profiles are represented by a single value (i.e., the centroid). While being effective in reducing the data size, centroiding also reduces the level of information density present in the mass peak profile. Moreover, each step of the centroiding process and their consequences on the final results may not be completely clear. Here, we present Cent2Prof, a package containing two algorithms that enables the conversion of the centroided data to mass peak profile data and vice versa. The centroiding algorithm uses the resolution-based mass peak width parameter as the first guess

SUBMITTER: Samanipour S 

PROVIDER: S-EPMC8674881 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature