Limits...
A shortcut for multiple testing on the directed acyclic graph of gene ontology.

Saunders G, Stevens JR, Isom SC - BMC Bioinformatics (2014)

Bottom Line: Often, the large number of gene sets that are tested simultaneously require some sort of multiplicity correction to account for the multiplicity effect.The computational and power differences of the Short Focus Level procedure as compared to the original Focus Level procedure are demonstrated both through simulation and using real data.The Short Focus Level procedure shows a significant increase in computation speed over the original Focus Level procedure (as much as ~15,000 times faster).

View Article: PubMed Central - PubMed

Affiliation: Utah State University, Department of Mathematics & Statistics, Logan, Utah, USA. saundersg@byui.edu.

ABSTRACT

Background: Gene set testing has become an important analysis technique in high throughput microarray and next generation sequencing studies for uncovering patterns of differential expression of various biological processes. Often, the large number of gene sets that are tested simultaneously require some sort of multiplicity correction to account for the multiplicity effect. This work provides a substantial computational improvement to an existing familywise error rate controlling multiplicity approach (the Focus Level method) for gene set testing in high throughput microarray and next generation sequencing studies using Gene Ontology graphs, which we call the Short Focus Level.

Results: The Short Focus Level procedure, which performs a shortcut of the full Focus Level procedure, is achieved by extending the reach of graphical weighted Bonferroni testing to closed testing situations where restricted hypotheses are present, such as in the Gene Ontology graphs. The Short Focus Level multiplicity adjustment can perform the full top-down approach of the original Focus Level procedure, overcoming a significant disadvantage of the otherwise powerful Focus Level multiplicity adjustment. The computational and power differences of the Short Focus Level procedure as compared to the original Focus Level procedure are demonstrated both through simulation and using real data.

Conclusions: The Short Focus Level procedure shows a significant increase in computation speed over the original Focus Level procedure (as much as ~15,000 times faster). The Short Focus Level should be used in place of the Focus Level procedure whenever the logical assumptions of the Gene Ontology graph structure are appropriate for the study objectives and when either no a priori focus level of interest can be specified or the focus level is selected at a higher level of the graph, where the Focus Level procedure is computationally intractable.

Show MeSH
Closures of the GO graphs from Figure 1 where the filled nodes represent the different choices of the focus level.(a) Full bottom-up approach. (b) Intermediate focus level. (c) Full top-down approach.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
getmorefigures.php?uid=PMC4232707&req=5

Fig2: Closures of the GO graphs from Figure 1 where the filled nodes represent the different choices of the focus level.(a) Full bottom-up approach. (b) Intermediate focus level. (c) Full top-down approach.

Mentions: To demonstrate, consider the closures of each of the example GO graphs from Figure 1 as shown in Figure 2. In each case, the nodes above the focus level remain unchanged, while the creation of several sets not present in the original example GO graph (depicted with rounded rectangles) are required in order to close the graph under all possible unions from the focus level down. Since the closing of the graph is only required from the selected focus level down, it is clear from Figure 2 that the more offspring terms the focus level contains, the greater the number of sets that must be created to close the graph. Closing the graph can quickly become computationally infeasible in practice. Importantly, performing the full top-down approach as in panel (c) of Figure 2 is rarely possible in real applications due to the computational burden.Figure 2


A shortcut for multiple testing on the directed acyclic graph of gene ontology.

Saunders G, Stevens JR, Isom SC - BMC Bioinformatics (2014)

Closures of the GO graphs from Figure 1 where the filled nodes represent the different choices of the focus level.(a) Full bottom-up approach. (b) Intermediate focus level. (c) Full top-down approach.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4232707&req=5

Fig2: Closures of the GO graphs from Figure 1 where the filled nodes represent the different choices of the focus level.(a) Full bottom-up approach. (b) Intermediate focus level. (c) Full top-down approach.
Mentions: To demonstrate, consider the closures of each of the example GO graphs from Figure 1 as shown in Figure 2. In each case, the nodes above the focus level remain unchanged, while the creation of several sets not present in the original example GO graph (depicted with rounded rectangles) are required in order to close the graph under all possible unions from the focus level down. Since the closing of the graph is only required from the selected focus level down, it is clear from Figure 2 that the more offspring terms the focus level contains, the greater the number of sets that must be created to close the graph. Closing the graph can quickly become computationally infeasible in practice. Importantly, performing the full top-down approach as in panel (c) of Figure 2 is rarely possible in real applications due to the computational burden.Figure 2

Bottom Line: Often, the large number of gene sets that are tested simultaneously require some sort of multiplicity correction to account for the multiplicity effect.The computational and power differences of the Short Focus Level procedure as compared to the original Focus Level procedure are demonstrated both through simulation and using real data.The Short Focus Level procedure shows a significant increase in computation speed over the original Focus Level procedure (as much as ~15,000 times faster).

View Article: PubMed Central - PubMed

Affiliation: Utah State University, Department of Mathematics & Statistics, Logan, Utah, USA. saundersg@byui.edu.

ABSTRACT

Background: Gene set testing has become an important analysis technique in high throughput microarray and next generation sequencing studies for uncovering patterns of differential expression of various biological processes. Often, the large number of gene sets that are tested simultaneously require some sort of multiplicity correction to account for the multiplicity effect. This work provides a substantial computational improvement to an existing familywise error rate controlling multiplicity approach (the Focus Level method) for gene set testing in high throughput microarray and next generation sequencing studies using Gene Ontology graphs, which we call the Short Focus Level.

Results: The Short Focus Level procedure, which performs a shortcut of the full Focus Level procedure, is achieved by extending the reach of graphical weighted Bonferroni testing to closed testing situations where restricted hypotheses are present, such as in the Gene Ontology graphs. The Short Focus Level multiplicity adjustment can perform the full top-down approach of the original Focus Level procedure, overcoming a significant disadvantage of the otherwise powerful Focus Level multiplicity adjustment. The computational and power differences of the Short Focus Level procedure as compared to the original Focus Level procedure are demonstrated both through simulation and using real data.

Conclusions: The Short Focus Level procedure shows a significant increase in computation speed over the original Focus Level procedure (as much as ~15,000 times faster). The Short Focus Level should be used in place of the Focus Level procedure whenever the logical assumptions of the Gene Ontology graph structure are appropriate for the study objectives and when either no a priori focus level of interest can be specified or the focus level is selected at a higher level of the graph, where the Focus Level procedure is computationally intractable.

Show MeSH