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POEM: Identifying Joint Additive Effects on Regulatory Circuits.

Botzman M, Nachshon A, Brodt A, Gat-Viks I - Front Genet (2016)

Bottom Line: POEM is specifically designed to achieve high performance in the case of additive joint effects.Our study reveals widespread additive, trans-acting pairwise effects on gene modules, characterizes their organizational principles, and highlights high-order interconnections between modules within the immune signaling network.These analyses elucidate the central role of additive pairwise effect in regulatory circuits, and provide computational tools for future investigations into the interplay between eQTLs.

View Article: PubMed Central - PubMed

Affiliation: Department of Cell Research and Immunology, The George S. Wise Faculty of Life Sciences, Tel Aviv University Tel Aviv, Israel.

ABSTRACT

Motivation: Expression Quantitative Trait Locus (eQTL) mapping tackles the problem of identifying variation in DNA sequence that have an effect on the transcriptional regulatory network. Major computational efforts are aimed at characterizing the joint effects of several eQTLs acting in concert to govern the expression of the same genes. Yet, progress toward a comprehensive prediction of such joint effects is limited. For example, existing eQTL methods commonly discover interacting loci affecting the expression levels of a module of co-regulated genes. Such "modularization" approaches, however, are focused on epistatic relations and thus have limited utility for the case of additive (non-epistatic) effects.

Results: Here we present POEM (Pairwise effect On Expression Modules), a methodology for identifying pairwise eQTL effects on gene modules. POEM is specifically designed to achieve high performance in the case of additive joint effects. We applied POEM to transcription profiles measured in bone marrow-derived dendritic cells across a population of genotyped mice. Our study reveals widespread additive, trans-acting pairwise effects on gene modules, characterizes their organizational principles, and highlights high-order interconnections between modules within the immune signaling network. These analyses elucidate the central role of additive pairwise effect in regulatory circuits, and provide computational tools for future investigations into the interplay between eQTLs.

Availability: The software described in this article is available at csgi.tau.ac.il/POEM/.

No MeSH data available.


Performance analysis of the POEM algorithm using synthetic data. Shown is the accuracy score (y-axis) over synthetic datasets that were generated using an additive (A,B) or epistasis (co-adaptive; C,D) model with different numbers of individuals (A,C; effect size = 0.6) or different effect sizes (B,D, 50 individuals; x-axis). The plots demonstrate the improved performance of POEM compared to the alternative methods.
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Figure 2: Performance analysis of the POEM algorithm using synthetic data. Shown is the accuracy score (y-axis) over synthetic datasets that were generated using an additive (A,B) or epistasis (co-adaptive; C,D) model with different numbers of individuals (A,C; effect size = 0.6) or different effect sizes (B,D, 50 individuals; x-axis). The plots demonstrate the improved performance of POEM compared to the alternative methods.

Mentions: We next extended the comparison to modularization methods (in addition to the single-trait analysis). Specifically, we investigated the performance of three residual-based methods, namely “RBSR,” “POEM,” and “Non-iterative POEM,” compared to the “PBM.” We found that all three residual-based methods outperformed the partition-based approach when applied to an additive model (P < 0.0008, 0.0004, 0.0004, respectively; paired t-test; Figures 2A,B), but not necessarily in the epistasis model (Figures 2C,D), as expected. Supplementary Figure 3 further indicates that the residual-based methods attain their best performance in the case of additive pairwise effects, unlike the PBM. These results support the use of residual-based mapping in the additive case.


POEM: Identifying Joint Additive Effects on Regulatory Circuits.

Botzman M, Nachshon A, Brodt A, Gat-Viks I - Front Genet (2016)

Performance analysis of the POEM algorithm using synthetic data. Shown is the accuracy score (y-axis) over synthetic datasets that were generated using an additive (A,B) or epistasis (co-adaptive; C,D) model with different numbers of individuals (A,C; effect size = 0.6) or different effect sizes (B,D, 50 individuals; x-axis). The plots demonstrate the improved performance of POEM compared to the alternative methods.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4835676&req=5

Figure 2: Performance analysis of the POEM algorithm using synthetic data. Shown is the accuracy score (y-axis) over synthetic datasets that were generated using an additive (A,B) or epistasis (co-adaptive; C,D) model with different numbers of individuals (A,C; effect size = 0.6) or different effect sizes (B,D, 50 individuals; x-axis). The plots demonstrate the improved performance of POEM compared to the alternative methods.
Mentions: We next extended the comparison to modularization methods (in addition to the single-trait analysis). Specifically, we investigated the performance of three residual-based methods, namely “RBSR,” “POEM,” and “Non-iterative POEM,” compared to the “PBM.” We found that all three residual-based methods outperformed the partition-based approach when applied to an additive model (P < 0.0008, 0.0004, 0.0004, respectively; paired t-test; Figures 2A,B), but not necessarily in the epistasis model (Figures 2C,D), as expected. Supplementary Figure 3 further indicates that the residual-based methods attain their best performance in the case of additive pairwise effects, unlike the PBM. These results support the use of residual-based mapping in the additive case.

Bottom Line: POEM is specifically designed to achieve high performance in the case of additive joint effects.Our study reveals widespread additive, trans-acting pairwise effects on gene modules, characterizes their organizational principles, and highlights high-order interconnections between modules within the immune signaling network.These analyses elucidate the central role of additive pairwise effect in regulatory circuits, and provide computational tools for future investigations into the interplay between eQTLs.

View Article: PubMed Central - PubMed

Affiliation: Department of Cell Research and Immunology, The George S. Wise Faculty of Life Sciences, Tel Aviv University Tel Aviv, Israel.

ABSTRACT

Motivation: Expression Quantitative Trait Locus (eQTL) mapping tackles the problem of identifying variation in DNA sequence that have an effect on the transcriptional regulatory network. Major computational efforts are aimed at characterizing the joint effects of several eQTLs acting in concert to govern the expression of the same genes. Yet, progress toward a comprehensive prediction of such joint effects is limited. For example, existing eQTL methods commonly discover interacting loci affecting the expression levels of a module of co-regulated genes. Such "modularization" approaches, however, are focused on epistatic relations and thus have limited utility for the case of additive (non-epistatic) effects.

Results: Here we present POEM (Pairwise effect On Expression Modules), a methodology for identifying pairwise eQTL effects on gene modules. POEM is specifically designed to achieve high performance in the case of additive joint effects. We applied POEM to transcription profiles measured in bone marrow-derived dendritic cells across a population of genotyped mice. Our study reveals widespread additive, trans-acting pairwise effects on gene modules, characterizes their organizational principles, and highlights high-order interconnections between modules within the immune signaling network. These analyses elucidate the central role of additive pairwise effect in regulatory circuits, and provide computational tools for future investigations into the interplay between eQTLs.

Availability: The software described in this article is available at csgi.tau.ac.il/POEM/.

No MeSH data available.