DynSig: Modelling Dynamic Signaling Alterations along Gene Pathways for Identifying Differential Pathways
Abstract
:1. Introduction
2. Materials and Methods
2.1. Framework of DynSig for Pathway Analysis
2.2. Data Preparation
2.3. Modeling the Dynamics of Gene Links Using Markov Chain Model
2.3.1. Scoring Gene Links for the Disparity of Signaling Dynamics
2.3.2. Identifying Differentially Expressed Pathways
2.3.3. Principal Pattern of Signaling Dynamics Specific to a Cancer Type
2.4. Simulation Data Generation
3. Results
3.1. Simulation Data Study
3.2. Applications to Real-World Expression Data
3.2.1. Identification of Differentially Expressed Pathways
3.2.2. Gene Links Play Significant Roles in Pathway Activity
3.2.3. Principal Patterns of Pathways Reflect Abnormality of Signaling Dynamics in Cancer
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Method | TPR | FPR | FNR | ACC | PPV | MCC | AUC |
---|---|---|---|---|---|---|---|
ρ = 0.3 | |||||||
Our method | 56.40/48.30 | 7.90/9.30 | 43.60/51.70 | 74.25/69.50 | 88.51/85.84 | 52.32/42.66 | 87.19/85.09 |
Global | 0.00/0.00 | 0.00/0.00 | 100.00/100.00 | 50.00/50.00 | NA/NA | NA/NA | 46.50/47.95 |
LRpath | 3.30/4.10 | 3.60/3.80 | 96.70/95.90 | 49.85/50.15 | 47.02/52.61 | −0.94/0.90 | 50.01/51.70 |
TAPPA | 5.80/7.30 | 3.40/2.70 | 94.20/92.70 | 51.20/52.30 | 61.96/72.08 | 5.47/10.29 | 58.37/63.05 |
Clipper | 0.20/1.00 | 0.50/1.70 | 99.80/99.00 | 49.85/49.65 | NA/32.33 | NA/−3.38 | 46.11/48.71 |
DEGraph | 1.80/2.20 | 2.00/2.20 | 98.20/97.80 | 49.90/50.00 | 46.67/47.33 | −0.79/−0.31 | 46.74/48.05 |
ρ = 0.5 | |||||||
Our method | 96.70/94.10 | 5.80/9.10 | 3.30/5.90 | 95.45/92.50 | 94.61/91.84 | 91.30/85.67 | 99.69/98.24 |
Global | 0.00/0.00 | 0.00/0.00 | 100.00/100.00 | 50.00/50.00 | NA/NA | NA/NA | 46.96/48.29 |
LRpath | 2.40/4.00 | 4.70/4.70 | 97.60/96.00 | 48.85/49.65 | 32.59/46.33 | −6.40/−1.67 | 49.87/50.26 |
TAPPA | 8.80/4.50 | 2.40/1.60 | 91.20/95.50 | 53.20/51.45 | 77.12/72.25 | 13.48/8.11 | 70.07/63.95 |
Clipper | 0.30/1.20 | 0.80/1.50 | 99.70/98.80 | 49.75/49.85 | NA/48.00 | NA/−0.71 | 47.43/47.30 |
DEGraph | 1.80/2.40 | 2.20/2.10 | 98.20/97.60 | 49.80/50.15 | NA/54.99 | NA/1.00 | 46.93/47.28 |
ρ = 0.7 | |||||||
Our method | 100.00/99.90 | 6.40/8.60 | 0.00/0.10 | 96.80/95.65 | 94.21/92.32 | 93.90/91.76 | 99.95/99.18 |
Global | 0.00/0.00 | 0.00/0.00 | 100.00/100.00 | 50.00/50.00 | NA/NA | NA/NA | 43.38/44.64 |
LRpath | 3.30/3.50 | 5.30/5.60 | 96.70/96.50 | 49.00/48.95 | 36.85/36.46 | −5.19/−5.40 | 49.94/48.92 |
TAPPA | 19.30/2.20 | 0.60/0.40 | 80.70/97.80 | 59.35/50.90 | 97.20/NA | 31.26/NA | 87.69/63.11 |
Clipper | 0.10/1.00 | 0.50/2.00 | 99.90/99.00 | 49.80/49.50 | NA/24.88 | NA/−4.92 | 44.28/44.61 |
DEGraph | 1.50/1.80 | 2.40/2.40 | 98.50/98.20 | 49.55/49.70 | 32.64/35.48 | −3.91/−3.01 | 44.98/47.14 |
Pathway | Our Method | Global Test | LRpath | TAPPA | Clipper | DEGraph |
---|---|---|---|---|---|---|
Axon guidance | √ | √ | ☓ | √ | √ | √ |
Cell cycle | √ | √ | √ | ☓ | √ | √ |
Chronic myeloid leukemia | √ | √ | ☓ | ☓ | √ | √ |
ErbB signaling pathway | ☓ | √ | ☓ | ☓ | ☓ | √ |
Neurotrophin signaling pathway | √ | √ | ☓ | ☓ | √ | √ |
Pathogenic Escherichia coli infection | √ | √ | ☓ | ☓ | √ | √ |
Pathways in cancer | √ | √ | ☓ | ☓ | ☓ | √ |
Shigellosis | √ | √ | ☓ | ☓ | √ | ☓ |
Viral myocarditis | √ | ☓ | √ | ☓ | √ | ☓ |
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Share and Cite
Shi, M.; Chong, Y.; Shen, W.; Xie, X.-P.; Wang, H.-Q. DynSig: Modelling Dynamic Signaling Alterations along Gene Pathways for Identifying Differential Pathways. Genes 2018, 9, 323. https://doi.org/10.3390/genes9070323
Shi M, Chong Y, Shen W, Xie X-P, Wang H-Q. DynSig: Modelling Dynamic Signaling Alterations along Gene Pathways for Identifying Differential Pathways. Genes. 2018; 9(7):323. https://doi.org/10.3390/genes9070323
Chicago/Turabian StyleShi, Ming, Yanwen Chong, Weiming Shen, Xin-Ping Xie, and Hong-Qiang Wang. 2018. "DynSig: Modelling Dynamic Signaling Alterations along Gene Pathways for Identifying Differential Pathways" Genes 9, no. 7: 323. https://doi.org/10.3390/genes9070323