Target-Decoy Search Strategy for Mass Spectrometry-Based Proteomics

By Joshua E. Elias, Steven P. Gygi. Proteome Bioinformatics, 2010

616 citations recorded by the source corpus.

Accurate and precise methods for estimating incorrect peptide and protein identifications are crucial for effective large-scale proteome analyses by tandem mass spectrometry. The target-decoy search strategy has emerged as a simple, effective tool for generating such estimations. This strategy is based on the premise that obvious, necessarily incorrect “decoy” sequences added to the search space will correspond with incorrect search results that might otherwise be deemed to be correct. With this knowledge, it is possible not only to estimate how many incorrect results are in a final data set but also to use decoy hits to guide the design of filtering criteria that sensitively partition a data set into correct and incorrect identifications.

Subfields: Molecular Biology, Spectroscopy

View Paper: https://www.semanticscholar.org/paper/c283bf27e550b8d82ca84923fd846bf8eabf2bd6

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Citations in the corpus

Scrublet: Computational Identification of Cell Doublets in Single-Cell Transcriptomic Data (2018, methodology): “With these assumptions, we show that doublets simulated from empirical datasets can be used to construct a “target-decoy” (Elias and Gygi, 2010) k-nearest neighbor (KNN) classifier capable of identifying doublets, as shown schematically in Figure 1C (Bayesian classifier derived in STAR Methods).”
Inaugural Article: The protein expression landscape of the Arabidopsis root (2012, positive): “thaliana reference protein database TAIR9 (TAIR, release 9), concatenated with a decoy database (the reversed TAIR9 database) to estimate the overall FDR (62, 63), plus roughly 260 additional known contaminants (i.”