title: Feature detection with controlled error rates in LC/MS images.
abstract: The Median M-N rule is a feature detection algorithm to detect peptide signals in Liquid Chromatography/Mass Spectrometry (LC/MS) images. As the procedure does not adequately control the statistical errors, we investigate an extension of the Median M-N rule to compute a statistical bound on the false-positive rate. We then study the false-negative rate and provide insights on the types of signal that can be detected by the M-N rule and the limit of detection. The resulting feature detection algorithm, which we term Quantile M-N rule, can be used in most feature detection algorithms to provide statistical control of the false-positive and false-negative rate.
authors.affiliation: CMLA, ENS Cachan, CNRs, Univer Sud, Cachan, France. Sebastien.Lithiaote@cmla.ens-cachan.fr
authors.forename: Sébastien
authors.initials: S
authors.lastname: Li-Thiao-Té
authors.forename: Benno
authors.initials: B
authors.lastname: Schwikowski
mesh_terms: D000465:Algorithms; D002853:Chromatography, Liquid / Q000379:methods*; D013058:Mass Spectrometry / Q000379:methods*; D015233:Models, Statistical; D010455:Peptides / Q000737:chemistry*
chemical_list: D010455:Peptides