Automatic analysis of agarose gel images.
BACKGROUND
Automatic tools to speed up routine biological processes are very much sought after in bio-medical research. Much repetitive work in molecular biology, such as allele calling in genetic analysis, can be made semi-automatic or task specific automatic by using existing techniques from computer science and signal processing. Computerized analysis is reproducible and avoids various forms of human error. Semi-automatic techniques with an interactive check on the results speed up the analysis and reduce the error.


RESULTS
We have successfully implemented an image processing software package to automatically analyze agarose gel images of polymorphic DNA markers. We have obtained up to 90% accuracy for the classification of alleles in good quality images and up to 70% accuracy in average quality images. These results are obtained within a few seconds. Even after subsequent interactive checking to increase the accuracy of allele classification to 100%, the overall speed with which the data can be processed is greatly increased, compared to manual allele classification.


BACKGROUND
The IDL source code of the software is available on request from jonathan.flint@well.ox.ac.uk
Adiga
P S
PS
Psychiatric Genetics Group, Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Headington, Oxford OX3 7BN, UK.
Bhomra
A
A
Turri
M G
MG
Nicod
A
A
Datta
S R
SR
Jeavons
P
P
Mott
R
R
Flint
J
J
D000818:Animals; D019295:Computational Biology; D004247:DNA / Q000235:genetics* / Q000302:isolation & purification*; D004587:Electrophoresis, Agar Gel / Q000706:statistics & numerical data*; D005819:Genetic Markers; D007091:Image Processing, Computer-Assisted / Q000706:statistics & numerical data*; D011110:Polymorphism, Genetic; D017422:Sequence Analysis, DNA / Q000706:statistics & numerical data; D012984:Software; D012985:Software Design
D005819:Genetic Markers; D004247:DNA