SMOOTH: a statistical method for successful removal of genotyping errors from high-density genetic linkage data (original) (raw)

Abstract

High-density genetic linkage maps can be used for purposes such as fine-scale targeted gene cloning and anchoring of physical maps. However, their construction is significantly complicated by even relatively small amounts of scoring errors. Currently available software is not able to solve the ordering ambiguities in marker clusters, which inhibits the application of high-density maps. A statistical method named SMOOTH was developed to remove genotyping errors from genetic linkage data during the mapping process. The program SMOOTH calculates the difference between the observed and predicted values of data points based on data points of neighbouring loci in a given marker order. Highly improbable data points are removed by the program in an iterative process with a mapping algorithm that recalculates the map after cleaning. SMOOTH has been tested with simulated data and experimental mapping data from potato. The simulations prove that this method is able to detect a high amount of scoring errors and demonstrates that the program enables mapping software to successfully construct a very accurate high-density map. In potato the application of the program resulted in a reliable placement of nearly 1,000 markers in one linkage group.

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Acknowledgements

We are very grateful to Dr. Fred van Eeuwijk for providing valuable comments. This work was carried out under the EU FAIR programme grant: FAIR5-PL97-3565.

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Authors and Affiliations

1. Laboratory of Plant Breeding, Wageningen University, P.O. Box 386, 6700 AJ, Wageningen, The Netherlands
   Hans van Os, Piet Stam, Richard G. F. Visser & Herman J. van Eck

Authors

1. Hans van Os
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2. Piet Stam
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3. Richard G. F. Visser
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4. Herman J. van Eck
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Corresponding author

Correspondence toHerman J. van Eck.

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Communicated by G. Wenzel

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van Os, H., Stam, P., Visser, R.G.F. et al. SMOOTH: a statistical method for successful removal of genotyping errors from high-density genetic linkage data.Theor Appl Genet 112, 187–194 (2005). https://doi.org/10.1007/s00122-005-0124-y

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• Received: 12 August 2004
• Accepted: 28 October 2004
• Published: 01 December 2005
• Issue Date: December 2005
• DOI: https://doi.org/10.1007/s00122-005-0124-y

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