Improved identification and quantification of peptides in mass spectrometry data via chemical and random additive noise elimination (CRANE).

ABSTRACT:

Motivation

The output of electrospray ionization-liquid chromatography mass spectrometry (ESI-LC-MS) is influenced by multiple sources of noise and major contributors can be broadly categorized as baseline, random and chemical noise. Noise has a negative impact on the identification and quantification of peptides, which influences the reliability and reproducibility of MS-based proteomics data. Most attempts at denoising have been made on either spectra or chromatograms independently, thus, important 2D information is lost because the mass-to-charge ratio and retention time dimensions are not considered jointly.

Results

This article presents a novel technique for denoising raw ESI-LC-MS data via 2D undecimated wavelet transform, which is applied to proteomics data acquired b

SUBMITTER: Seneviratne AJ 

PROVIDER: S-EPMC8711017 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature