Titel
Model-based probe set optimization for high-performance microarrays
Autor*in
David P. Kreil
Universität für Bodenkultur Wien
Autor*in
Karl Bayer
Universität für Bodenkultur Wien
... show all
Abstract
A major challenge in microarray design is the selection of highly specific oligonucleotide probes for all targeted genes of interest, while maintaining thermodynamic uniformity at the hybridization temperature. We introduce a novel microarray design framework (Thermodynamic Model-based Oligo Design Optimizer, TherMODO) that for the first time incorporates a number of advanced modelling features: (i) A model of position-dependent labelling effects that is quantitatively derived from experiment. (ii) Multi-state thermodynamic hybridization models of probe binding behaviour, including potential cross-hybridization reactions. (iii) A fast calibrated sequence-similarity-based heuristic for cross-hybridization prediction supporting large-scale designs. (iv) A novel compound score formulation for the integrated assessment of multiple probe design objectives. In contrast to a greedy search for probes meeting parameter thresholds, this approach permits an optimization at the probe set level and facilitates the selection of highly specific probe candidates while maintaining probe set uniformity. (v) Lastly, a flexible target grouping structure allows easy adaptation of the pipeline to a variety of microarray application scenarios. The algorithm and features are discussed and demonstrated on actual design runs. Source code is available on request.
Objekt-Typ
Sprache
Englisch [eng]
Persistent identifier
https://phaidra.univie.ac.at/o:243968
Erschienen in
Titel
Nucleic Acids Research
Band
37
Ausgabe
3
Seitenanfang
e18
Erscheinungsdatum
01.01.2009
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