AutomRm: An R Package for Fully Automatic LC-QQQ-MS Data Preprocessing Powered by Machine Learning.

ABSTRACT: Preprocessing of liquid chromatography-mass spectrometry (LC-MS) raw data facilitates downstream statistical and biological data analyses. In the case of targeted LC-MS data, consistent recognition of chromatographic peaks is a main challenge, in particular, for low abundant signals. Fully automatic preprocessing is faster than manual peak review and does not depend on the individual operator. Here, we present the R package automRm for fully automatic preprocessing of LC-MS data recorded in MRM mode. Using machine learning (ML) for detection of chromatographic peaks and quality control of reported results enables the automatic recognition of complex patterns in raw data. In addition, this approach renders automRm generally applicable to a wide range of analytical methods including hydrophi

SUBMITTER: Eilertz D 

PROVIDER: S-EPMC9047440 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature