Using Peptide-Level Proteomics Data for Detecting Differentially Expressed Proteins

The expression of proteins can be quantified in high-throughput means using different types of mass spectrometers. In recent years, there have emerged label-free methods for determining protein abundance. Although the expression is initially measured at the peptide level, a common approach is to com...

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Bibliographic Details
Published in:Journal of proteome research 2015-11, Vol.14 (11), p.4564-4570
Main Authors: Suomi, Tomi, Corthals, Garry L, Nevalainen, Olli S, Elo, Laura L
Format: Article
Language:English
Subjects:
Gene Expression Regulation
Internet
Peptide Fragments - analysis
Peptide Fragments - genetics
Peptide Fragments - metabolism
Proteins - genetics
Proteins - metabolism
Proteolysis
Proteomics - methods
Sensitivity and Specificity
Software
Trypsin - chemistry
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Summary:The expression of proteins can be quantified in high-throughput means using different types of mass spectrometers. In recent years, there have emerged label-free methods for determining protein abundance. Although the expression is initially measured at the peptide level, a common approach is to combine the peptide-level measurements into protein-level values before differential expression analysis. However, this simple combination is prone to inconsistencies between peptides and may lose valuable information. To this end, we introduce here a method for detecting differentially expressed proteins by combining peptide-level expression-change statistics. Using controlled spike-in experiments, we show that the approach of averaging peptide-level expression changes yields more accurate lists of differentially expressed proteins than does the conventional protein-level approach. This is particularly true when there are only few replicate samples or the differences between the sample groups are small. The proposed technique is implemented in the Bioconductor package PECA, and it can be downloaded from http://www.bioconductor.org.
ISSN:1535-3893
1535-3907
DOI:10.1021/acs.jproteome.5b00363