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PAGER: constructing PAGs and new PAG-PAG relationships for network biology.

Yue Z, Kshirsagar MM, Nguyen T, Suphavilai C, Neylon MT, Zhu L, Ratliff T, Chen JY - Bioinformatics (2015)

Bottom Line: To help users assess each PAG's biological relevance, we developed a cohesion measure called Cohesion Coefficient (CoCo), which is capable of disambiguating between biologically significant PAGs and random PAGs with an area-under-curve performance of 0.98.PAGER database was set up to help users to search and retrieve PAGs from its online web interface.PAGER enable advanced users to build PAG-PAG regulatory networks that provide complementary biological insights not found in gene set analysis or individual gene network analysis.

View Article: PubMed Central - PubMed

Affiliation: Indiana University School of Informatics and Computing, Department of Computer and Information Science, Indiana University-Purdue University Indianapolis, Indianapolis, IN 46202, Purdue University Center for Cancer Research, West Lafayette, IN 47906 and Institute of Biopharmaceutical Informatics and Technology, Wenzhou Medical University, WenZhou, Zhe Jiang Province, China.

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Cohesions (CoI, CoT and CoCo) performance: (a) ROC curves, (b) comparison boxplot. CoI+, CoI in the true PAGs; CoI−, CoI in the random PAGs; CoT+, CoT in the true PAGs; CoT−, CoT in the random PAGs
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btv265-F3: Cohesions (CoI, CoT and CoCo) performance: (a) ROC curves, (b) comparison boxplot. CoI+, CoI in the true PAGs; CoI−, CoI in the random PAGs; CoT+, CoT in the true PAGs; CoT−, CoT in the random PAGs

Mentions: We evaluated PAG classification performance (biological relevant YES/NO classes) using three different PAG cohesion measures, i.e. CoI, CoT and CoCo. First, using the ROC curve (Fig. 3), we observed that all these measures can classify true PAGs from randomly generated PAGs effectively. The area-under-curves (AUCs) of classification performance for balanced positive class (integrated PAGs from the PAGER database) and negative class (randomly generated PAGs) are 0.96, 0.95 and 0.98 respectively for each of the cohesion measures CoI, CoT and CoCo. Second, we compared the positive class with the negative class using these cohesion measures’ score distributions. Measurement score distributions between samples from the two classes are statistically significant at P-values of 8.5e-138 (for CoI), 3.0e-10 (for CoT) and 2.4e-62 (for CoCo), respectively, when two-sample t-test analysis is used. Third, we observed variable effects between PAG size and cohesion measurements’ classification performance. For example, the AUC performance using CoT is slightly better than that for CoI among small PAGs (n < 100), based on Table 2. These observation justifies the use of the combined score CoCo whenever CoT may be calculated (size>2 and minimal PPI triangle = 1).Fig. 3.


PAGER: constructing PAGs and new PAG-PAG relationships for network biology.

Yue Z, Kshirsagar MM, Nguyen T, Suphavilai C, Neylon MT, Zhu L, Ratliff T, Chen JY - Bioinformatics (2015)

Cohesions (CoI, CoT and CoCo) performance: (a) ROC curves, (b) comparison boxplot. CoI+, CoI in the true PAGs; CoI−, CoI in the random PAGs; CoT+, CoT in the true PAGs; CoT−, CoT in the random PAGs
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4553834&req=5

btv265-F3: Cohesions (CoI, CoT and CoCo) performance: (a) ROC curves, (b) comparison boxplot. CoI+, CoI in the true PAGs; CoI−, CoI in the random PAGs; CoT+, CoT in the true PAGs; CoT−, CoT in the random PAGs
Mentions: We evaluated PAG classification performance (biological relevant YES/NO classes) using three different PAG cohesion measures, i.e. CoI, CoT and CoCo. First, using the ROC curve (Fig. 3), we observed that all these measures can classify true PAGs from randomly generated PAGs effectively. The area-under-curves (AUCs) of classification performance for balanced positive class (integrated PAGs from the PAGER database) and negative class (randomly generated PAGs) are 0.96, 0.95 and 0.98 respectively for each of the cohesion measures CoI, CoT and CoCo. Second, we compared the positive class with the negative class using these cohesion measures’ score distributions. Measurement score distributions between samples from the two classes are statistically significant at P-values of 8.5e-138 (for CoI), 3.0e-10 (for CoT) and 2.4e-62 (for CoCo), respectively, when two-sample t-test analysis is used. Third, we observed variable effects between PAG size and cohesion measurements’ classification performance. For example, the AUC performance using CoT is slightly better than that for CoI among small PAGs (n < 100), based on Table 2. These observation justifies the use of the combined score CoCo whenever CoT may be calculated (size>2 and minimal PPI triangle = 1).Fig. 3.

Bottom Line: To help users assess each PAG's biological relevance, we developed a cohesion measure called Cohesion Coefficient (CoCo), which is capable of disambiguating between biologically significant PAGs and random PAGs with an area-under-curve performance of 0.98.PAGER database was set up to help users to search and retrieve PAGs from its online web interface.PAGER enable advanced users to build PAG-PAG regulatory networks that provide complementary biological insights not found in gene set analysis or individual gene network analysis.

View Article: PubMed Central - PubMed

Affiliation: Indiana University School of Informatics and Computing, Department of Computer and Information Science, Indiana University-Purdue University Indianapolis, Indianapolis, IN 46202, Purdue University Center for Cancer Research, West Lafayette, IN 47906 and Institute of Biopharmaceutical Informatics and Technology, Wenzhou Medical University, WenZhou, Zhe Jiang Province, China.

Show MeSH
Related in: MedlinePlus