MS-EmpiRe Utilizes Peptide-level Noise Distributions for Ultra-sensitive Detection of Differentially Expressed Proteins.

ABSTRACT: Mass spectrometry based proteomics is the method of choice for quantifying genome-wide differential changes of protein expression in a wide range of biological and biomedical applications. Protein expression changes need to be reliably derived from many measured peptide intensities and their corresponding peptide fold changes. These peptide fold changes vary considerably for a given protein. Numerous instrumental setups aim to reduce this variability, whereas current computational methods only implicitly account for this problem. We introduce a new method, MS-EmpiRe, which explicitly accounts for the noise underlying peptide fold changes. We derive data set-specific, intensity-dependent empirical error fold change distributions, which are used for individual weighing of peptide fold change

SUBMITTER: Ammar C 

PROVIDER: S-EPMC6731086 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature