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GeneTIER: prioritization of candidate disease genes using tissue-specific gene expression profiles.

Antanaviciute A, Daly C, Crinnion LA, Markham AF, Watson CM, Bonthron DT, Carr IM - Bioinformatics (2015)

Bottom Line: Since systematic experimental verification of each such candidate gene is not feasible, a method is needed to decide which genes are worth investigating further.Computational gene prioritization presents itself as a solution to this problem, systematically analyzing and sorting each gene from the most to least likely to be the disease-causing gene, in a fraction of the time it would take a researcher to perform such queries manually.Here, we present Gene TIssue Expression Ranker (GeneTIER), a new web-based application for candidate gene prioritization.

View Article: PubMed Central - PubMed

Affiliation: Section of Genetics, Institute of Biomedical and Clinical Sciences, School of Medicine, University of Leeds, St James's University Hospital and.

No MeSH data available.


Related in: MedlinePlus

ROC curve showing classifier performance on different size input generated using disease genes from the benchmarking dataset (see Section 2)
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btv196-F2: ROC curve showing classifier performance on different size input generated using disease genes from the benchmarking dataset (see Section 2)

Mentions: Figure 2 shows the resultant ROC graphs while Table 1 shows the corresponding AUC scores. This analysis suggests that the algorithm’s performance was inversely related to the number of non-disease genes in the analysis, but does not decline in a linear manner. In fact, the differences in performance when assessed on candidate lists consisting of 100, 200 or 500 candidates are minor and do not suggest that the maximum candidate gene list size will be encountered in typical gene mapping experiments. Overall, the obtained AUC values are sufficiently high to suggest that disease genes are typically ranked higher than the randomly selected genes in each data set by this algorithm.Table 1.


GeneTIER: prioritization of candidate disease genes using tissue-specific gene expression profiles.

Antanaviciute A, Daly C, Crinnion LA, Markham AF, Watson CM, Bonthron DT, Carr IM - Bioinformatics (2015)

ROC curve showing classifier performance on different size input generated using disease genes from the benchmarking dataset (see Section 2)
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4528628&req=5

btv196-F2: ROC curve showing classifier performance on different size input generated using disease genes from the benchmarking dataset (see Section 2)
Mentions: Figure 2 shows the resultant ROC graphs while Table 1 shows the corresponding AUC scores. This analysis suggests that the algorithm’s performance was inversely related to the number of non-disease genes in the analysis, but does not decline in a linear manner. In fact, the differences in performance when assessed on candidate lists consisting of 100, 200 or 500 candidates are minor and do not suggest that the maximum candidate gene list size will be encountered in typical gene mapping experiments. Overall, the obtained AUC values are sufficiently high to suggest that disease genes are typically ranked higher than the randomly selected genes in each data set by this algorithm.Table 1.

Bottom Line: Since systematic experimental verification of each such candidate gene is not feasible, a method is needed to decide which genes are worth investigating further.Computational gene prioritization presents itself as a solution to this problem, systematically analyzing and sorting each gene from the most to least likely to be the disease-causing gene, in a fraction of the time it would take a researcher to perform such queries manually.Here, we present Gene TIssue Expression Ranker (GeneTIER), a new web-based application for candidate gene prioritization.

View Article: PubMed Central - PubMed

Affiliation: Section of Genetics, Institute of Biomedical and Clinical Sciences, School of Medicine, University of Leeds, St James's University Hospital and.

No MeSH data available.


Related in: MedlinePlus