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Single-feature polymorphism discovery by computing probe affinity shape powers.

Xu WW, Cho S, Yang SS, Bolon YT, Bilgic H, Jia H, Xiong Y, Muehlbauer GJ - BMC Genet. (2009)

Bottom Line: Single-feature polymorphism (SFP) discovery is a rapid and cost-effective approach to identify DNA polymorphisms.This method was validated by known sequence information and was comprehensively compared with previously-reported methods using the same datasets.The 364 SFPs discovered in a barley near-isogenic line pair provide a set of genetic markers for fine mapping and future map-based cloning of the Cul2 locus.

View Article: PubMed Central - HTML - PubMed

Affiliation: Supercomputing Institute for Advanced Computational Research, University of Minnesota, Minnesota, MN 55455, USA. wxu@msi.umn.edu

ABSTRACT

Background: Single-feature polymorphism (SFP) discovery is a rapid and cost-effective approach to identify DNA polymorphisms. However, high false positive rates and/or low sensitivity are prevalent in previously described SFP detection methods. This work presents a new computing method for SFP discovery.

Results: The probe affinity differences and affinity shape powers formed by the neighboring probes in each probe set were computed into SFP weight scores. This method was validated by known sequence information and was comprehensively compared with previously-reported methods using the same datasets. A web application using this algorithm has been implemented for SFP detection. Using this method, we identified 364 SFPs in a barley near-isogenic line pair carrying either the wild type or the mutant uniculm2 (cul2) allele. Most of the SFP polymorphisms were identified on chromosome 6H in the vicinity of the Cul2 locus.

Conclusion: This SFP discovery method exhibits better performance in specificity and sensitivity over previously-reported methods. It can be used for other organisms for which GeneChip technology is available. The web-based tool will facilitate SFP discovery. The 364 SFPs discovered in a barley near-isogenic line pair provide a set of genetic markers for fine mapping and future map-based cloning of the Cul2 locus.

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Detection accuracy performances. Precision-Recall (PR) curve shows precision levels (y-axis) at different Recalls (or true positive rate TPR, x-axis). PASP line (blue), PILM (red), and PAOP (black) were plotted by 8, 10, and 9 selected weight score cutoffs (Additional file 4). The points with the best performances are indicated by red stars and the cutoff values reported in original methods are indicated by black stars. The Areas Under the Curve (AUC) were indicated by the bar chart.
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Figure 2: Detection accuracy performances. Precision-Recall (PR) curve shows precision levels (y-axis) at different Recalls (or true positive rate TPR, x-axis). PASP line (blue), PILM (red), and PAOP (black) were plotted by 8, 10, and 9 selected weight score cutoffs (Additional file 4). The points with the best performances are indicated by red stars and the cutoff values reported in original methods are indicated by black stars. The Areas Under the Curve (AUC) were indicated by the bar chart.

Mentions: We calculated the Precision-Recall (PR) curve [48] to further examine the performances at different weight score cutoffs. As seen in Figure 2, curves tending to the upper-right-hand corner exhibit better performance. The 2.5 cutoff point on the PASP line (Figure 2, blue line, star) shows the highest performance compared to all other points on the PASP line.


Single-feature polymorphism discovery by computing probe affinity shape powers.

Xu WW, Cho S, Yang SS, Bolon YT, Bilgic H, Jia H, Xiong Y, Muehlbauer GJ - BMC Genet. (2009)

Detection accuracy performances. Precision-Recall (PR) curve shows precision levels (y-axis) at different Recalls (or true positive rate TPR, x-axis). PASP line (blue), PILM (red), and PAOP (black) were plotted by 8, 10, and 9 selected weight score cutoffs (Additional file 4). The points with the best performances are indicated by red stars and the cutoff values reported in original methods are indicated by black stars. The Areas Under the Curve (AUC) were indicated by the bar chart.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2746803&req=5

Figure 2: Detection accuracy performances. Precision-Recall (PR) curve shows precision levels (y-axis) at different Recalls (or true positive rate TPR, x-axis). PASP line (blue), PILM (red), and PAOP (black) were plotted by 8, 10, and 9 selected weight score cutoffs (Additional file 4). The points with the best performances are indicated by red stars and the cutoff values reported in original methods are indicated by black stars. The Areas Under the Curve (AUC) were indicated by the bar chart.
Mentions: We calculated the Precision-Recall (PR) curve [48] to further examine the performances at different weight score cutoffs. As seen in Figure 2, curves tending to the upper-right-hand corner exhibit better performance. The 2.5 cutoff point on the PASP line (Figure 2, blue line, star) shows the highest performance compared to all other points on the PASP line.

Bottom Line: Single-feature polymorphism (SFP) discovery is a rapid and cost-effective approach to identify DNA polymorphisms.This method was validated by known sequence information and was comprehensively compared with previously-reported methods using the same datasets.The 364 SFPs discovered in a barley near-isogenic line pair provide a set of genetic markers for fine mapping and future map-based cloning of the Cul2 locus.

View Article: PubMed Central - HTML - PubMed

Affiliation: Supercomputing Institute for Advanced Computational Research, University of Minnesota, Minnesota, MN 55455, USA. wxu@msi.umn.edu

ABSTRACT

Background: Single-feature polymorphism (SFP) discovery is a rapid and cost-effective approach to identify DNA polymorphisms. However, high false positive rates and/or low sensitivity are prevalent in previously described SFP detection methods. This work presents a new computing method for SFP discovery.

Results: The probe affinity differences and affinity shape powers formed by the neighboring probes in each probe set were computed into SFP weight scores. This method was validated by known sequence information and was comprehensively compared with previously-reported methods using the same datasets. A web application using this algorithm has been implemented for SFP detection. Using this method, we identified 364 SFPs in a barley near-isogenic line pair carrying either the wild type or the mutant uniculm2 (cul2) allele. Most of the SFP polymorphisms were identified on chromosome 6H in the vicinity of the Cul2 locus.

Conclusion: This SFP discovery method exhibits better performance in specificity and sensitivity over previously-reported methods. It can be used for other organisms for which GeneChip technology is available. The web-based tool will facilitate SFP discovery. The 364 SFPs discovered in a barley near-isogenic line pair provide a set of genetic markers for fine mapping and future map-based cloning of the Cul2 locus.

Show MeSH