title: AutoDecon, a deconvolution algorithm for identification and characterization of luteinizing hormone secretory bursts: description and validation using synthetic data.
abstract: Hormone signaling is often pulsatile, and multiparameter deconvolution procedures have long been used to identify and characterize secretory events. However, the existing programs have serious limitations, including the subjective nature of initial peak selection, lack of statistical verification of presumed bursts, and user-unfriendliness of the application. Here we describe a novel deconvolution program, AutoDecon, which addresses these concerns. We validate AutoDecon for application to serum luteinizing hormone (LH) concentration time series using synthetic data mimicking real data from normal women and then comparing the performance of AutoDecon with the performance of the widely employed hormone pulsatility analysis program Cluster. The sensitivity of AutoDecon is higher than that of Cluster ( approximately 96% vs. 80%, P=0.001). However, Cluster had a lower false-positive detection rate than did AutoDecon (6% vs. 1%, P=0.001). Further analysis demonstrated that the pulsatility parameters recovered by AutoDecon were indistinguishable from those characterizing the synthetic data and that sampling at 5- or 10-min intervals was optimal for maximizing the sensitivity rates for LH. Accordingly, AutoDecon presents a viable nonsubjective alternative to previous pulse detection algorithms for the analysis of LH data. It is applicable to other pulsatile hormone concentration time series and many other pulsatile phenomena. The software is free and downloadable at http://mljohnson.pharm.virginia.edu/home.html.
authors.affiliation: Department of Pharmacology, University of Virginia, Charlottesville, VA 22908, USA. mlj8e@virginia.edu
authors.forename: Michael L
authors.initials: ML
authors.lastname: Johnson
authors.forename: Lenore
authors.initials: L
authors.lastname: Pipes
authors.forename: Paula P
authors.initials: PP
authors.lastname: Veldhuis
authors.forename: Leon S
authors.initials: LS
authors.lastname: Farhy
authors.forename: David G
authors.initials: DG
authors.lastname: Boyd
authors.forename: William S
authors.initials: WS
authors.lastname: Evans
mesh_terms: D000328:Adult; D000465:Algorithms; D000818:Animals; D005189:False Positive Reactions; D005260:Female; D007987:Gonadotropin-Releasing Hormone / Q000097:blood; D006207:Half-Life; D006801:Humans; D007986:Luteinizing Hormone / Q000097:blood / Q000378:metabolism*; D008597:Menstrual Cycle / Q000097:blood; D008875:Middle Aged; D008954:Models, Biological; D017698:Postmenopause / Q000097:blood; D017697:Premenopause / Q000097:blood; D015203:Reproducibility of Results; D012756:Sheep; D012984:Software; D013997:Time Factors
chemical_list: D007987:Gonadotropin-Releasing Hormone; D007986:Luteinizing Hormone