Sign in
BioinformaticsPLoS ONE
Peer-reviewed journal article

False discovery rate estimation and heterobifunctional cross-linkers

Lutz FischeriD, Juri RappsilberiD

Abstract

False discovery rate (FDR) estimation is a cornerstone of proteomics that has recently been adapted to cross-linking/mass spectrometry. Here we demonstrate that heterobifunctional cross-linkers, while theoretically different from homobifunctional cross-linkers, need not be considered separately in practice. We develop and then evaluate the impact of applying a correct FDR formula for use of heterobifunctional cross-linkers and conclude that there are minimal practical advantages. Hence a single formula can be applied to data generated from the many different non-cleavable cross-linkers.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers
Citations
22
FWCI
1.08
Field percentile
top 28%

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISMatzinger '22Fischer '24Lenz '21Chen '22Lin '24Zhou '22
59% semantic matchBioinformatics
Manuel Matzinger, Adrian Vasiu, Mathias Madalinski+3 more·Nature Communications·Jul 8, 2022· 27 citations