Automatic context-sensitive karyotyping of human chromosomes based on elliptically symmetric statistical distributions

We introduce a statistical model of a metaphase cell consisting of independent chromosomes with elliptically symmetric feature vectors. From this model we derive the ML-classifier for classification in the 24 chromosomal classes, taking into account the correct number of chromosomes in each class. Experimental results show that error rates of the best of these classifiers are less than 2% with respect to chromosomes if applied to the large Copenhagen data set Cpr. Simulation studies suggest that there should be even more information contained in the features of this data set.

[1]  Keinosuke Fukunaga,et al.  Introduction to Statistical Pattern Recognition , 1972 .

[2]  R. E. Slot.  On the profit of taking into account the known number of objects per class in classification methods (Corresp.) , 1979, IEEE Trans. Inf. Theory.

[3]  S. Kotz,et al.  Symmetric Multivariate and Related Distributions , 1989 .

[4]  Jim Piper,et al.  Improved chromosome classification using monotonic functions of mahalanobis distance and the transportation method , 1994, Math. Methods Oper. Res..

[5]  J D Habbema,et al.  A discriminant analysis approach to the identification of human chromosomes. , 1976, Biometrics.

[6]  Jim Piper.  The effect of zero feature correlation assumption on maximum likelihood based classification of chromosomes , 1987 .

[7]  Carl W. Lee,et al.  Transportation problems which can be solved by the use of hirsch-paths for the dual problems , 1987, Math. Program..

[8]  Jim Graham,et al.  The transportation algorithm as an aid to chromosome classification , 1983, Pattern Recognit. Lett..

[9]  Douglas M. Hawkins,et al.  Elements of Continuous Multivariate Analysis , 1969 .

[10]  Erik Granum.  Application of Statistical and Syntactical Methods of Analysis and Classification to Chromosome Data , 1982 .

[11]  Michel Balinski,et al.  Signature Methods for the Assignment Problem , 1985, Oper. Res..

[12]  J. Piper,et al.  On fully automatic feature measurement for banded chromosome classification. , 1989, Cytometry.

[13]  Jim Piper,et al.  Automation of chromosome analysis , 1980 .

[14]  J D Habbema,et al.  Statistical methods for classification of human chromosomes. , 1979, Biometrics.

[15]  Jim Graham,et al.  An efficient transportation algorithm for automatic chromosome karyotyping , 1991, Pattern Recognit. Lett..

[16]  E Granum,et al.  Visual classification of banded human chromosomes: , 1977, Annals of human genetics.

[17]  A D Carothers,et al.  Some methods of combining class information in multivariate normal discrimination for the classification of human chromosomes. , 1991, Statistics in medicine.

[18]  F. Arrighi,et al.  Automated homologue matching of human G-banded chromosomes. , 1986, Computers in biology and medicine.

[19]  Jim Piper,et al.  Variability and bias in experimentally measured classifier error rates , 1992, Pattern Recognit. Lett..

[20]  E Granum,et al.  Visual classification of banded human chromosomes I. Karyotyping compared with classification of isolated chromosomes , 1976, Annals of human genetics.