title: The multidimensional perturbation value: a single metric to measure similarity and activity of treatments in high-throughput multidimensional screens.
abstract: Screens using high-throughput, information-rich technologies such as microarrays, high-content screening (HCS), and next-generation sequencing (NGS) have become increasingly widespread. Compared with single-readout assays, these methods produce a more comprehensive picture of the effects of screened treatments. However, interpreting such multidimensional readouts is challenging. Univariate statistics such as t-tests and Z-factors cannot easily be applied to multidimensional profiles, leaving no obvious way to answer common screening questions such as "Is treatment X active in this assay?" and "Is treatment X different from (or equivalent to) treatment Y?" We have developed a simple, straightforward metric, the multidimensional perturbation value (mp-value), which can be used to answer these questions. Here, we demonstrate application of the mp-value to three data sets: a multiplexed gene expression screen of compounds and genomic reagents, a microarray-based gene expression screen of compounds, and an HCS compound screen. In all data sets, active treatments were successfully identified using the mp-value, and simulations and follow-up analyses supported the mp-value's statistical and biological validity. We believe the mp-value represents a promising way to simplify the analysis of multidimensional data while taking full advantage of its richness.
authors.affiliation: Novartis Institutes for Biomedical Research, Cambridge, MA 02139, USA. jannahutz@gmail.com
authors.forename: Janna E
authors.initials: JE
authors.lastname: Hutz
authors.forename: Thomas
authors.initials: T
authors.lastname: Nelson
authors.forename: Hua
authors.initials: H
authors.lastname: Wu
authors.forename: Gregory
authors.initials: G
authors.lastname: McAllister
authors.forename: Ioannis
authors.initials: I
authors.lastname: Moutsatsos
authors.forename: Savina A
authors.initials: SA
authors.lastname: Jaeger
authors.forename: Somnath
authors.initials: S
authors.lastname: Bandyopadhyay
authors.forename: Florian
authors.initials: F
authors.lastname: Nigsch
authors.forename: Ben
authors.initials: B
authors.lastname: Cornett
authors.forename: Jeremy L
authors.initials: JL
authors.lastname: Jenkins
authors.forename: Douglas W
authors.initials: DW
authors.lastname: Selinger
mesh_terms: D003198:Computer Simulation; D057166:High-Throughput Screening Assays / Q000379:methods*; D006801:Humans; D006877:Hydroxamic Acids / Q000494:pharmacology; D061986:MCF-7 Cells; D025341:Principal Component Analysis; D013223:Statistics as Topic
chemical_list: D006877:Hydroxamic Acids; C012589:trichostatin A