ArticleJournal of proteome research2017
Param-Medic: A Tool for Improving MS/MS Database Search Yield by Optimizing Parameter Settings.
Article in Journal of proteome research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Automatic Selection of Search Parameter Values for Mass Spectrometry-Based Search Engines.Journal of proteome research · 2026Article
- Genomic, Proteomic, and Biochemical Study ofJournal of agricultural and food chemistry · 2025Article
- Identification of Proteoforms Related toProteomes · 2025Article
- Proteome-Wide Identification of RNA-dependent proteins and an emerging role for RNAs in Plasmodium falciparum protein complexes.Nature communications · 2024Article
- The Crux Toolkit for Analysis of Bottom-Up Tandem Mass Spectrometry Proteomics Data.Journal of proteome research · 2023Article
- Improving Peptide-Level Mass Spectrometry Analysis via Double Competition.Journal of proteome research · 2022Article
- Improving the Genome Annotation ofCurrent genomics · 2021Article
- Accurately Assigning Peptides to Spectra When Only a Subset of Peptides Are Relevant.Journal of proteome research · 2021Article
- mokapot: Fast and Flexible Semisupervised Learning for Peptide Detection.Journal of proteome research · 2021Article
- More Accurate Transcript Assembly via Parameter Advising.Journal of computational biology : a journal of computational molecular cell biology · 2020Article
- Bioinformatics Methods for Mass Spectrometry-Based Proteomics Data Analysis.International journal of molecular sciences · 2020Review
- Machine Learning Strategy That Leverages Large Data sets to Boost Statistical Power in Small-Scale Experiments.Journal of proteome research · 2020Article
- Detecting Modifications in Proteomics Experiments with Param-Medic.Journal of proteome research · 2019Article
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Authors and funding
3 authors.
Funding
Abstract
In shotgun proteomics analysis, user-specified parameters are critical to database search performance and therefore to the yield of confident peptide-spectrum matches (PSMs). Two of the most important parameters are related to the accuracy of the mass spectrometer. Precursor mass tolerance defines the peptide candidates considered for each spectrum. Fragment mass tolerance or bin size determines how close observed and theoretical fragments must be to be considered a match. For either of these two parameters, too wide a setting yields randomly high-scoring false PSMs, whereas too narrow a setting erroneously excludes true PSMs, in both cases, lowering the yield of peptides detected at a given false discovery rate. We describe a strategy for inferring optimal search parameters by assembling and analyzing pairs of spectra that are likely to have been generated by the same peptide ion to infer precursor and fragment mass error. This strategy does not rely on a database search, making it usable in a wide variety of settings. In our experiments on data from a variety of instruments including Orbitrap and Q-TOF acquisitions, this strategy yields more high-confidence PSMs than using settings based on instrument defaults or determined by experts. Param-Medic is open-source and cross-platform. It is available as a standalone tool ( http://noble.gs.washington.edu/proj/param-medic/ ) and has been integrated into the Crux proteomics toolkit ( http://crux.ms ), providing automatic parameter selection for the Comet and Tide search engines.
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