Signatures for Mass Spectrometry Data Quality, part 4 of 5

ABSTRACT: Logistic regression classification models were fit to manually classified quality control (QC) LC-MS/MS datasets to develop a model that can predict whether a dataset is in or out of control. Model parameters were optimized by minimizing a loss function that accounts for the tradeoff between false positive and false negative errors. In addition to the 1152 training/testing datasets, we are including 2662 additional datasets, all of the same QC sample (whole cell lysate of Shewanella oneidensis). Datasets originate from 6 Thermo instrument platforms: Exactive, LTQ, VelosPro, Orbitrap, Q-Exactive, and Velos Orbitrap.

INSTRUMENT(S): LTQ Orbitrap Velos

ORGANISM(S): Shewanella Oneidensis (strain Mr-1)

SUBMITTER: Matthew Monroe  

PROVIDER: PXD000323 | Pride | 2013-10-04

REPOSITORIES: Pride