Bioinformatics Advance Access published November 16, 2004
BIOINFORMATICS
CyDAS: A Cytogenetic Data Analysis System
Bernhard Hiller1, Jutta Bradtke1, Harald Balz1 and Harald Rieder1,2,*
1
Institut für Klinische Genetik der Phillipps-Universität Marburg,
Bahnhofstr. 7, 35037 Marburg, Germany
2
Institut für Humangenetik und Anthropologie, Universitätsklinikum Düsseldorf,
Universitätsstr. 1, 40225 Düsseldorf, Germany
Metaphase chromosome analysis is a well established tool
for the investigation of the genetic changes in tumors. It
provides an overview of the genomic alterations on a single
cell level and is, therefore, unexcelled for the detection of
cell clones carrying different chromosome changes in tumor
tissues. In tumors, which display chromosomally distinct
cell populations, the timely order of the occurrence of
chromosome aberrations can be investigated. The time point
of the occurrence of particular chromosome aberrations during tumor progression can also be estimated by the correlation of the frequency of the respective chromosomal change
in a cohort of tumors with the number of alterations of the
karyotypes (Hoglund et al., 2001; Hoglund et al., 2002).
Both approaches provide clues to the chromosomal pathways of the tumor progression. The identification of recurring chromosome breakpoints and/or the delineation of
minimal regions of chromosome gains or losses may point
to the chromosomal localization of genes which are important for the development of the tumor in focus of the investigation (Cooper, 1996).
The chromosomal aberrations are inferred from banding
patterns and written down using the International System for
Human Cytogenetic Nomenclature (ISCN, 1995) The text
strings of the ISCN karyotypes display the chromosome
changes as single aberration events. In karyotypes, which
contain unbalanced translocations or complexly rearranged
chromosomes, the chromosomal gains and/or losses are not
*
To whom correspondence should be addressed.
Bioinformatics © Oxford University Press 2004; all rights reserved.
directly deducible from the respective ISCN string. This
information becomes evident only if the entire karyotype is
considered and, therefore, represents metainformation. Due
to technical reasons, the resolution of the chromosome
banding and the accurateness of the chromosome changes
may differ between different tumor samples. To improve the
access to the karyotype metainformation and to normalize
the chromosome banding resolution for statistical evaluations, a simplified computer readable cytogenetic nomenclature (SCCN) was developed. Using SCCN, qualitative and
quantitative aberrations are written separately and explicitly
and, thus, can be easily used as an input for computer programs (Bradtke et al., 2003). However, no automated procedure for the translation of ISCN karyotypes into SCCN
strings has been available, as yet.
Only a few approaches have been undertaken to develop
programs for an automated analysis of ISCN karyotypes. In
the 1980ies, a computer program was presented which determined types of aberrations and breakpoints as well as
gains and losses of whole chromosomes (Kamada et al,
1983; Hashimoto et al, 1989). The extraction of the metainformation from the ISCN formula, i.e. the gains and losses
of chromosomal fragments implied by the aberrations, was
not possible. Recently, two internet applications were
launched which address the conversion of ISCN karyotypes
into computer accessible data formats. The KaryoReader
calculates a list of gains, losses and structural aberrations
per chromosome band (Liang, 2004). The Karyotype Cytoband Table Converter draws bars according to the cumulative gains and losses next to ideograms. A table containing
the data on chromosome band level is available (Baudis,
2004). Complex chromosome aberrations are not adequately
processed, which may lead to erroneous results. Neither
program seems to be intended for integration into desk top
applications.
Here we describe a new application, which analyses single aberrations, single karyotypes and large sets of karyotype data. It can be accessed online via the internet, and a
desktop version – which is available for download - runs on
common Windows computers.
The business logic is packed in a class library (dot net assembly). Its major entrance point is the Karyotype class,
Downloaded from http://bioinformatics.oxfordjournals.org/ at Pennsylvania State University on May 16, 2016
ABSTRACT
For statistical analyses in cancer cytogenetics, the genomic
changes encoded by the karyotype must be translated into
numerical codes. We developed a program, which extracts
chromosomal gains and losses as well as breakpoints from
the karyotype. The changes are compiled in tables according
to the chromosome bands involved and/or depicted in projection to the respective chromosome ideogram. The data
are ready to be integrated into further statistical analyses.
The program may be run as desktop or internet application.
Availability: http://www.cydas.org/
Contact: [email protected]
Hiller et al.
• ISCN Analysis analyses a single karyotype. It shows
virtually all information, which can be extracted from
an ISCN formula. In case of an error, the program will
show the first erroneous element and a description of
the error. This feature is useful for quality management
of the cytogenetic data: Some 10% of the entries in the
Mitelman database – which is based on published data
only – contain errors (Hiller et al., 2004).
• Drawing aberrant chromosomes draws ideograms for
derivative chromosomes. After entering the description
of the aberrant chromosome in ISCN style, the desired
banding resolution is selected. Distinct colors for each
chromosomal origin are used. With such ideograms the
cytogenetic descriptions of aberrant chromosomes can
be visually checked.
• Analysing Mitelman Data graphically analyses large
data sets downloaded from the Mitelman database of
chromosome aberrations in cancer (Mitelman et al.,
2004). A text file is uploaded which contains the chromosome data retrieved by a database query. Several parameters can be selected, which, e.g., define the way of
the processing of uncertainties of chromosome findings, the level of banding resolution, and the settings
for the graphical visualization. The program calculates
the amount of aberrations and of gains and losses per
chromosomal band .The results are displayed as columns projecting to the respective chromosome ideograms and are also available as a table, which can be
used in data mining approaches. Furthermore, a commented list of the errors is presented which were found
in the karyotypes.
2
Desktop versions of these programs can also be
downloaded. They run on common computers with current
versions of Microsoft Windows and the Dot Net framework.
An integration into common Microsoft Access databases is
possible.
For people interested in writing their own programs, a
large set of documentation and how-to documents is available online.
ACKNOWLEDGEMENTS
This work was supported by a grant of the Deutsche Forschungsgemeinschaft, RI 1123/2-1 (DFG).
REFERENCES
Bradtke,J., Balz,H., Fonatsch,C., Heinze,B., Jauch,A., Mohr,B.,
Schoch,C. and Rieder,H. (2003) Computer aided analysis of
additional chromosome aberrations in Philadelphia chromosome positive acute lymphoblastic leukaemia using a simplified
computer readable cytogenetic notation. BMC Bioinformatics 4;
4.
Baudis,M. (2004) Karyotype cytoband table converter.
http://www.progenetix.de/felixtest.html
Cooper,C.S. (1996) Translocations in solid tumours. Curr Opin
Genet Dev; 6, 71-75.
Hashimoto,T., Kamada,N., Yamamoto,H. and Munaka,M. (1989)
A computer program for analysis of chromosome abnormalities.
Nippon Ketsueki Gakkai Zasshi, 52, 38-48.
Hiller,B., Bradtke,J., Balz,H. and Rieder,H. (2004) ISCNAnalyzer
easily detects karyotype errors in cytogenetic databases. European Journal of Human Genetics, 12 (S1), 128-129
Hoglund,M., Gisselsson,D., Sall,T. and Mitelman,F. (2002) Coping with complexity. multivariate analysis of tumor karyotypes.
Cancer Genet Cytogenet, 135 (2), 103-109.
Hoglund,M., Sall,T., Heim,S., Mitelman,F., Mandahl,N., and FadlElmula,I. (2001) Identification of cytogenetic subgroups and
karyotypic pathways in transitional cell carcinoma. Cancer Res;
61 (22), 8241-8246.
ISCN (1995) An International System for Human Cytogenetic
Nomenclature. Mitelman,F. (ed.) S Karger, Basel
Kamada,N., Yamamoto,H., Tanaka,K., Ohtaki,M., Ueoka,H.,
Munaka,M. and Kuramoto,A. (1983) Analysis and rearrangement of human karyotypes by computer. Cancer Genet
Cytogenet, 10, 17-22.
Liang,P. (2004) KaryoReader. http://falcon.roswellpark.org/KR/
Mitelman,F., Johansson,B., Mertens,F. (Eds.) (2004) Mitelman
Database of Chromosome Aberrations in Cancer.
http://cgap.nci.nih.gov/Chromosomes/Mitelman
Downloaded from http://bioinformatics.oxfordjournals.org/ at Pennsylvania State University on May 16, 2016
which analyses a single karyotype. The analysis of the aberration elements is delegated to the Aberration class, with
one Aberration object for each aberration element. The Aberration object calculates the structural aberrations, gains
and losses for the aberration. The QuantitativeAberrations
and QualitativeAberrations objects returned from the Aberration objects are summed up by the Karyotype object. Such
QuantitativeAberrations and QualitativeAberrations objects
can be summed up for several karyotypes. From them, an
object showing gains, losses and structural aberrations per
chromosomal band can be calculated. The CyDASGraphics
class uses such an object as input for generating bitmaps
representing these data. From these figures, recurring aberrations – both structural and numeric – , and chromosomal
imbalances can be seen easily.
Since information on human chromosomal structure is
placed into an xml file, karyotypes of other species whose
cytogenetic nomenclature is compatible with human nomenclature can be analyzed when that file is replaced.
On the CyDAS web site, three programs showing useful
examples of the employment of the class library for typical
cytogenetic tasks can be accessed online.