Trace2PS and FSA2PS: two software toolkits for converting trace and fsa files to PostScript format.
BACKGROUND
Due to the advanced techniques in sequencing and fragment analysis, DNA sequencers and analyzers produce vast amounts of data within short time. To administrate the large data volume conveniently, efficient data management systems are used in order to process and to store sequencers' or analyzers' data outcome. The inclusion of graphical reports in such systems is necessary to achieve a comprehensive view of the integrated data. However, the resulting data of sequencing and fragment analysis runs are stored in a proprietary format, the so-called trace or fsa format, which is only readable by programs provided by the instrument's vendor operating on the machine itself or by commercial tools designed for editing the respective data. To allow for a quick conversion of the proprietary data format into a commonly used one, toolkits are required that reach this aim and can be easily integrated into workflow systems.


RESULTS
We have developed the software toolkits Trace2PS and Fsa2PS which allow to convert sequence and fragment analysis raw data files to PostScript images, respectively. The toolkits are implemented as Perl modules that can be used as standalone command line applications in conjunction with a script-based analysis pipeline, or integrated in software applications for displaying the data content of trace and fsa files. The converter modules support the commonly used file formats for storage of sequencing (ABI and SCF) and fragment analysis data (FSA).


CONCLUSIONS
The software toolkits provide useful applications to convert sequencing and fragment analysis files from a proprietary into a more common, human-readable format. Trace2PS and FSA2PS are useful and capable in data management workflow systems like SAMS, or laboratory information systems that are used for displaying trace and fragment analysis results via web-based tools over an intranet or internet connection to users that can view their results directly on the screen.
Krawczyk
Justina
J
Computational Genomics, Center for Biotechnology (CeBiTec), 33594 Bielefeld, Germany. jkrawczy@cebitec.uni-bielefeld.de.
Goesmann
Alexander
A
Nolte
Ralf
R
Werber
Martin
M
Weisshaar
Bernd
B