title: Bringing statistics up to speed with data in analysis of lymphocyte motility.
abstract: Two-photon (2P) microscopy provides immunologists with 3D video of the movement of lymphocytes in vivo. Motility parameters extracted from these videos allow detailed analysis of lymphocyte motility in lymph nodes and peripheral tissues. However, standard parametric statistical analyses such as the Student's t-test are often used incorrectly, and fail to take into account confounds introduced by the experimental methods, potentially leading to erroneous conclusions about T cell motility. Here, we compare the motility of WT T cell versus PKCθ-/-, CARMA1-/-, CCR7-/-, and PTX-treated T cells. We show that the fluorescent dyes used to label T cells have significant effects on T cell motility, and we demonstrate the use of factorial ANOVA as a statistical tool that can control for these effects. In addition, researchers often choose between the use of "cell-based" parameters by averaging multiple steps of a single cell over time (e.g. cell mean speed), or "step-based" parameters, in which all steps of a cell population (e.g. instantaneous speed) are grouped without regard for the cell track. Using mixed model ANOVA, we show that we can maintain cell-based analyses without losing the statistical power of step-based data. We find that as we use additional levels of statistical control, we can more accurately estimate the speed of T cells as they move in lymph nodes as well as measure the impact of individual signaling molecules on T cell motility. As there is increasing interest in using computational modeling to understand T cell behavior in in vivo, these quantitative measures not only give us a better determination of actual T cell movement, they may prove crucial for models to generate accurate predictions about T cell behavior.
authors.affiliation: Department of Molecular Genetics and Microbiology, University of New Mexico School of Medicine, Albuquerque, NM, United States of America; Department of Computer Science, University of New Mexico, Albuquerque, NM, United States of America.
authors.forename: Kenneth
authors.initials: K
authors.lastname: Letendre
authors.affiliation: Inserm, U1016, Institut Cochin, Université Paris Descartes, Sorbonne Paris Cité, Paris, France.
authors.forename: Emmanuel
authors.initials: E
authors.lastname: Donnadieu
authors.affiliation: Department of Computer Science, University of New Mexico, Albuquerque, NM, United States of America; Department of Biology, University of New Mexico, Albuquerque, NM, United States of America; Santa Fe Institute, Santa Fe, New Mexico, United States of America.
authors.forename: Melanie E
authors.initials: ME
authors.lastname: Moses
authors.affiliation: Department of Molecular Genetics and Microbiology, University of New Mexico School of Medicine, Albuquerque, NM, United States of America.
authors.forename: Judy L
authors.initials: JL
authors.lastname: Cannon
mesh_terms: D000704:Analysis of Variance; D000818:Animals; D053468:CARD Signaling Adaptor Proteins / Q000032:analysis / Q000235:genetics; D002465:Cell Movement; D005456:Fluorescent Dyes / Q000378:metabolism; D017353:Gene Deletion; D007527:Isoenzymes / Q000032:analysis / Q000235:genetics; D008198:Lymph Nodes / Q000166:cytology; D008214:Lymphocytes / Q000166:cytology* / Q000187:drug effects / Q000378:metabolism; D008810:Mice, Inbred C57BL; D036641:Microscopy, Fluorescence, Multiphoton; D061848:Optical Imaging; D011493:Protein Kinase C / Q000032:analysis / Q000235:genetics; D000074121:Protein Kinase C-theta; D054400:Receptors, CCR7 / Q000032:analysis / Q000235:genetics
chemical_list: D053468:CARD Signaling Adaptor Proteins; C496467:Card11 protein, mouse; D005456:Fluorescent Dyes; D007527:Isoenzymes; D054400:Receptors, CCR7; C489593:Prkcq protein, mouse; D011493:Protein Kinase C; D000074121:Protein Kinase C-theta