Journal of Proteome ResearchBioinformaticsPeer-reviewed journal article
Quality control for the target decoy approach for peptide identification
Elke Debrie, Milan MalfaitiD, Ralf GabrielsiD, Arthur Declerq, Adriaan StickeriD, Lennart MartensiD, Lieven ClementiD
Abstract
Reliable peptide identification is key in mass spectrometry (MS) based proteomics. To this end, the target-decoy approach (TDA) has become the cornerstone for extracting a set of reliable peptide-to-spectrum matches (PSMs) that will be used in downstream analysis. Indeed, TDA is now the default method to estimate the false discovery rate (FDR) for a given set of PSMs, and users typically view it as a universal solution for assessing the FDR in the peptide identification step. However, the TDA also relies on a minimal set of assumptions, which are typically never verified in practice. We argue that a violation of these assumptions can lead to poor FDR control, which can be detrimental to any downstream data analysis. We here therefore first clearly spell out these TDA assumptions, and introduce TargetDecoy, a Bioconductor package with all the necessary functionality to control the TDA quality and its underlying assumptions for a given set of PSMs. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/516857v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@fed04borg.highwire.dtl.DTLVardef@11d115dorg.highwire.dtl.DTLVardef@15f1a45org.highwire.dtl.DTLVardef@b5ceab_HPS_FORMAT_FIGEXP M_FIG C_FIG
- assay: proteomics
- research focus: software / tool
- research focus: benchmarking
- approach: statistical model
- Citations
- 11
- FWCI
- 1.01
- Field percentile
- top 32%
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