An exact algorithm for finding cancer driver somatic genome alterations: the weighted mutually exclusive maximum set cover problem

Abstract

BackgroundThe mutual exclusivity of somatic genome alterations (SGAs), such as somatic mutations and copy number alterations, is an important observation of tumors and is widely used to search for cancer signaling pathways or SGAs related to tumor development. However, one problem with current methods that use mutual exclusivity is that they are not signal-based; another problem is that they use heuristic algorithms to handle the NP-hard problems, which cannot guarantee to find the optimal solutions of their models.MethodIn this study, we propose a novel signal-based method that utilizes the intrinsic relationship between SGAs on signaling pathways and expression changes of downstream genes regulated by pathways to identify cancer signaling pathways using the mutually exclusive property. We also present a relatively efficient exact algorithm that can guarantee to obtain the optimal solution of the new computational model.ResultsWe have applied our new model and exact algorithm to the breast cancer data. The results reveal that our new approach increases the capability of finding better solutions in the application of cancer research. Our new exact algorithm has a time complexity of (Note: Following the recent convention, we use a star * to represent that the polynomial part of the time complexity is neglected), which has solved the NP-hard problem of our model efficiently.ConclusionOur new method and algorithm can discover the true causes behind the phenotypes, such as what SGA events lead to abnormality of the cell cycle or make the cell metastasis lose control in tumors; thus, it identifies the target candidates for precision (or target) therapeutics.Electronic supplementary materialThe online version of this article (doi:10.1186/s13015-016-0073-9) contains supplementary material, which is available to authorized users.

Effective Use of Water and Increased Dry Matter Partitioned to Grain Contribute to Yield of Common Bean Improved for Drought Resistance

“…Increased WUE reduces the rate of transpiration and crop water use, processes that are crucial for carbon assimilation, biomass production, and yield (Blum, 2009 ; Sinclair, 2012 ). However, the reduction in water use is generally achieved by plant traits and environmental responses that could also reduce yield potential (Blum, 2005 ). WUE is a complex trait and difficult to phenotype, preventing many breeding programs from using WUE directly (Araus et al, 2002 ; Easlon et al, 2014 ).…”

Identifying driver genomic alterations in cancers by searching minimum-weight, mutually exclusive sets

“…As is the case with the formulations of other studies on mutual exclusivity [12][13][14]16,17], our problem is NP-hard (see the proof in a separate technical report [28]). Previous studies used heuristic or stochastic algorithms [12][13][14]16,17] to handle the mutually exclusive set cover problem or its variants, but such algorithms do not guarantee the finding of optimal solutions.…”

“…We improved the algorithm's running time by carefully selecting subsets in F for branching. As the proof of the algorithm is very involved, we present the details in the technical report [28]. We have implemented all algorithms for the paper.…”

Analogous Process Structure Induction for Sub-event Sequence Prediction

“…On one hand, the conceptualized event cannot be too general, as we do not want to lose touch with the original event, and, on the other hand, if it is too specific, we will not aggregate enough instances of sub-events into it, thus we will have difficulties transferring knowledge to the new unseen process. To automatically achieve the balance between these conflicting requirements and select the best abstract event for each observed sub-event, we model it as a weighted mutually exclusive set cover problem (Lu and Lu, 2014) and propose an efficient algorithm, described below, to solve it. We then merge the repeated conceptualized events and determine their relative positions.…”