Signalling pathway impact analysis based on the strength of interaction between genes

Abstract

Signalling pathway analysis is a popular approach that is used to identify significant cancer-related pathways based on differentially expressed genes (DEGs) from biological experiments. The main advantage of signalling pathway analysis lies in the fact that it assesses both the number of DEGs and the propagation of signal perturbation in signalling pathways. However, this method simplifies the interactions between genes by categorising them only as activation (+1) and suppression (-1), which does not encompass the range of interactions in real pathways, where interaction strength between genes may vary. In this study, the authors used newly developed signalling pathway impact analysis (SPIA) methods, SPIA based on Pearson correlation coefficient (PSPIA), and mutual information (MSPIA), to measure the interaction strength between pairs of genes. In analyses of a colorectal cancer dataset, a lung cancer dataset, and a pancreatic cancer dataset, PSPIA and MSPIA identified more candidate cancer-related pathways than were identified by SPIA. Generally, MSPIA performed better than PSPIA.

Signaling Pathway Analysis Combined With the Strength Variations of Interactions Between Genes Under Different Conditions

“…Ullah used the t-value of a gene produced by the limma R package instead of the fold-change of the gene used in SPIA [13]. Bao et al used the Pearson correlation coefficients or mutual information to represent the strength of interactions between genes that in SPIA were +1 or -1 [14]. In another study, Li et al applied the minimum spanning tree method to find subpathways of signaling pathways and then used the SPIA method to identify significant subpathways [15].…”

Peer Review #2 of "Identifying disease-associated signaling pathways through a novel effector gene analysis (v0.1)"

“…Bao et al (2016) developed two SPIA-based methods called PSPIA and MSPIA. These two methods replaced +1 or -1 interaction strength in SPIA with the interaction strength of the Pearson correlation coefficients and mutual information, respectively (Bao et al 2016). There are different pathwaytopology methods that make use of the topological information of signaling pathways.…”

Identifying disease-associated signaling pathways through a novel effector gene analysis

“… Li et al (2015) developed a method called sub-SPIA, which used a minimum spanning tree way to prune signaling pathways and used the SPIA method to identify significant signaling subpathways ( Li et al, 2015 ). Bao et al (2016) developed two SPIA-based methods called PSPIA and MSPIA. These two methods replaced +1 or −1 interaction strength in SPIA with the interaction strength of the Pearson correlation coefficients and mutual information, respectively ( Bao et al, 2016 ).…”

“… Bao et al (2016) developed two SPIA-based methods called PSPIA and MSPIA. These two methods replaced +1 or −1 interaction strength in SPIA with the interaction strength of the Pearson correlation coefficients and mutual information, respectively ( Bao et al, 2016 ). There are different pathway-topology methods that make use of the topological information of signaling pathways.…”