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'N-of-1-pathways' unveils personal deregulated mechanisms from a single pair of RNA-Seq samples: towards precision medicine.

Gardeux V, Achour I, Li J, Maienschein-Cline M, Li H, Pesce L, Parinandi G, Bahroos N, Winn R, Foster I, Garcia JG, Lussier YA - J Am Med Inform Assoc (2014)

Bottom Line: Cross-patient N-of-1-pathways obtains comparable results with conventional genesets enrichment analysis (GSEA) and differentially expressed gene (DEG) enrichment, validated in three external evaluations.Patients were ranked based on the similarity of their deregulated mechanisms to those of an independent gold standard, generating unsupervised clusters of diametric extreme survival phenotypes (p=0.03).The N-of-1-pathways framework provides a robust statistical and relevant biological interpretation of individual disease-free survival that is often overlooked in conventional cross-patient studies.

View Article: PubMed Central - PubMed

Affiliation: Department of Medicine, Bio5 Institute, UA Cancer Center, University of Arizona, Tucson, Arizona, USA Department of Medicine, University of Illinois at Chicago, Chicago, Illinois, USA Department of Informatics, School of Engineering, EISTI (École Internationale des Sciences du Traitement de l'Information), Cergy-Pontoise, France Institute for Translational Health Informatics, University of Illinois at Chicago, Chicago, Illinois, USA.

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Synthetic data: evaluation of the size and ratio of concordant deregulated genes within a pathway required to be found deregulated in the N-of-1-pathways statistical analysis component. Each point represents one size of a simulated pathway generated by randomly selecting n genes and a ratio r of the deregulated genes within the pathway. The ratio r is artificially increased by a k-fold change in a simulated pathway seeded in the exploration dataset (k∈{1.3, 1.5, 2}). We then applied the N-of-1-pathways statistical analysis component to verify if the simulated pathway was found deregulated with a significance threshold (type I error) chosen as an unadjusted p value of ≤0.05. For each value (n, r, k), we repeated this procedure 1000 times in order to estimate the false negative rate (type II error β). Sim., simulated (see the ‘Theoretical results: validation using synthetic data’ section in the Methods).
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AMIAJNL2013002519F1: Synthetic data: evaluation of the size and ratio of concordant deregulated genes within a pathway required to be found deregulated in the N-of-1-pathways statistical analysis component. Each point represents one size of a simulated pathway generated by randomly selecting n genes and a ratio r of the deregulated genes within the pathway. The ratio r is artificially increased by a k-fold change in a simulated pathway seeded in the exploration dataset (k∈{1.3, 1.5, 2}). We then applied the N-of-1-pathways statistical analysis component to verify if the simulated pathway was found deregulated with a significance threshold (type I error) chosen as an unadjusted p value of ≤0.05. For each value (n, r, k), we repeated this procedure 1000 times in order to estimate the false negative rate (type II error β). Sim., simulated (see the ‘Theoretical results: validation using synthetic data’ section in the Methods).

Mentions: A synthetic geneset that contains a percentage of concordant deregulated genes was generated using the exploration dataset. Each point of figure 1 represents one geneset size of a simulated pathway varying from 15 to 500 genes by increments of 5 and generated by randomly selecting ‘n’ genes among the 20 502 reported in the exploration study. Further, a proportion of genes ‘r’ (ratio represented in %) involved in this synthetic geneset was considered deregulated. The expression of genes of the normal sample included in that ratio r was then artificially increased by a twofold change and assigned to the tumoral sample. This ratio was varied by 5% to 100% with increments of 5%. The hypothesis was stated as H0: ‘The geneset is not deregulated.’ For each pair (n, r), we applied the N-of-1-pathways statistical analysis component 1000 times in order to estimate the false negative rate (type II error β). This resampling was repeated for 1960 combinations of n and r. The type II errors reported in figure 1 were computed as the number of times the truly deregulated pathway of the simulation is not found deregulated (false negative) divided by 1000 (1 960 000 calculations of N-of-1-pathways calculated using the 150 teraflops, 18 000-core Beagle Cray XE6 supercomputer of the Computation Institute located at the Argonne National Laboratory). Since figure 1 focuses on cataloging the type II error according to one specifically sized pathway at a time, we considered a pathway significantly found deregulated by N-of-1-pathways when the unadjusted p value was ≤0.05.


'N-of-1-pathways' unveils personal deregulated mechanisms from a single pair of RNA-Seq samples: towards precision medicine.

Gardeux V, Achour I, Li J, Maienschein-Cline M, Li H, Pesce L, Parinandi G, Bahroos N, Winn R, Foster I, Garcia JG, Lussier YA - J Am Med Inform Assoc (2014)

Synthetic data: evaluation of the size and ratio of concordant deregulated genes within a pathway required to be found deregulated in the N-of-1-pathways statistical analysis component. Each point represents one size of a simulated pathway generated by randomly selecting n genes and a ratio r of the deregulated genes within the pathway. The ratio r is artificially increased by a k-fold change in a simulated pathway seeded in the exploration dataset (k∈{1.3, 1.5, 2}). We then applied the N-of-1-pathways statistical analysis component to verify if the simulated pathway was found deregulated with a significance threshold (type I error) chosen as an unadjusted p value of ≤0.05. For each value (n, r, k), we repeated this procedure 1000 times in order to estimate the false negative rate (type II error β). Sim., simulated (see the ‘Theoretical results: validation using synthetic data’ section in the Methods).
© Copyright Policy - open-access
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4215042&req=5

AMIAJNL2013002519F1: Synthetic data: evaluation of the size and ratio of concordant deregulated genes within a pathway required to be found deregulated in the N-of-1-pathways statistical analysis component. Each point represents one size of a simulated pathway generated by randomly selecting n genes and a ratio r of the deregulated genes within the pathway. The ratio r is artificially increased by a k-fold change in a simulated pathway seeded in the exploration dataset (k∈{1.3, 1.5, 2}). We then applied the N-of-1-pathways statistical analysis component to verify if the simulated pathway was found deregulated with a significance threshold (type I error) chosen as an unadjusted p value of ≤0.05. For each value (n, r, k), we repeated this procedure 1000 times in order to estimate the false negative rate (type II error β). Sim., simulated (see the ‘Theoretical results: validation using synthetic data’ section in the Methods).
Mentions: A synthetic geneset that contains a percentage of concordant deregulated genes was generated using the exploration dataset. Each point of figure 1 represents one geneset size of a simulated pathway varying from 15 to 500 genes by increments of 5 and generated by randomly selecting ‘n’ genes among the 20 502 reported in the exploration study. Further, a proportion of genes ‘r’ (ratio represented in %) involved in this synthetic geneset was considered deregulated. The expression of genes of the normal sample included in that ratio r was then artificially increased by a twofold change and assigned to the tumoral sample. This ratio was varied by 5% to 100% with increments of 5%. The hypothesis was stated as H0: ‘The geneset is not deregulated.’ For each pair (n, r), we applied the N-of-1-pathways statistical analysis component 1000 times in order to estimate the false negative rate (type II error β). This resampling was repeated for 1960 combinations of n and r. The type II errors reported in figure 1 were computed as the number of times the truly deregulated pathway of the simulation is not found deregulated (false negative) divided by 1000 (1 960 000 calculations of N-of-1-pathways calculated using the 150 teraflops, 18 000-core Beagle Cray XE6 supercomputer of the Computation Institute located at the Argonne National Laboratory). Since figure 1 focuses on cataloging the type II error according to one specifically sized pathway at a time, we considered a pathway significantly found deregulated by N-of-1-pathways when the unadjusted p value was ≤0.05.

Bottom Line: Cross-patient N-of-1-pathways obtains comparable results with conventional genesets enrichment analysis (GSEA) and differentially expressed gene (DEG) enrichment, validated in three external evaluations.Patients were ranked based on the similarity of their deregulated mechanisms to those of an independent gold standard, generating unsupervised clusters of diametric extreme survival phenotypes (p=0.03).The N-of-1-pathways framework provides a robust statistical and relevant biological interpretation of individual disease-free survival that is often overlooked in conventional cross-patient studies.

View Article: PubMed Central - PubMed

Affiliation: Department of Medicine, Bio5 Institute, UA Cancer Center, University of Arizona, Tucson, Arizona, USA Department of Medicine, University of Illinois at Chicago, Chicago, Illinois, USA Department of Informatics, School of Engineering, EISTI (École Internationale des Sciences du Traitement de l'Information), Cergy-Pontoise, France Institute for Translational Health Informatics, University of Illinois at Chicago, Chicago, Illinois, USA.

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Related in: MedlinePlus