MsImpute: Estimation of Missing Peptide Intensity Data in Label-Free Quantitative Mass Spectrometry.

ABSTRACT: Mass spectrometry (MS) enables high-throughput identification and quantification of proteins in complex biological samples and can provide insights into the global function of biological systems. Label-free quantification is cost-effective and suitable for the analysis of human samples. Despite rapid developments in label-free data acquisition workflows, the number of proteins quantified across samples can be limited by technical and biological variability. This variation can result in missing values which can in turn challenge downstream data analysis tasks. General purpose or gene expression-specific imputation algorithms are widely used to improve data completeness. Here, we propose an imputation algorithm designated for label-free MS data that is aware of the type of missingness affect

SUBMITTER: Hediyeh-Zadeh S 

PROVIDER: S-EPMC10368900 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature