A statistical model for unwarping of 1-D electrophoresis gels
Artikel i vetenskaplig tidskrift, 2005

A statistical model is proposed which relates density profiles in 1-D electrophoresis gels, such as those produced by pulsed-field gel electrophoresis (PFGE), to databases of profiles of known genotypes. The warp in each gel lane is described by a trend that is linear in its parameters plus a first-order autoregressive process, and density differences are modelled by a mixture of two normal distributions. Maximum likelihood estimates are computed efficiently by a recursive algorithm that alternates between dynamic time warping to align individual lanes and generalised-least-squares regression to ensure that the warp is smooth between lanes. The method, illustrated using PFGE of Escherichia coli O157 strains, automatically unwarps and classifies gel lanes, and facilitates manual identification of new genotypes.

Dynamic programming

Autoregressive process

Image warping

Mixture distribution

Pulsed-field gel electrophoresis

Författare

Chris Glasbey

Biomathematics & Statistics Scotland

Leila Vali

University of Edinburgh College of Medicine and Veterinary Medicine

John Gustafsson

Chalmers, Matematiska vetenskaper, matematisk statistik

Göteborgs universitet

Electrophoresis

0173-0835 (ISSN) 1522-2683 (eISSN)

Vol. 26 22 4237-4242

Ämneskategorier

Mikrobiologi inom det medicinska området

Sannolikhetsteori och statistik

Datorseende och robotik (autonoma system)

DOI

10.1002/elps.200500365