Predicted protein complexes


From a protein-protein interaction dataset by Collins et al., we predicted protein complexes and overlapping complexes using the method ClusterONE as described in Nepusz T, Yu H, Paccanaro A., Detecting overlapping protein complexes in protein-protein interaction networks. Nat Methods (2012).


DCP1-2


Nodes:
3
Quality:
0.715
Pval:
0.029

FYV10


Nodes:
6
Quality:
0.947
Pval:
0.002

MCD1


Nodes:
3
Quality:
1
Pval:
0.029

NUC1


Nodes:
3
Quality:
1
Pval:
0.029

SIR2


Nodes:
3
Quality:
1
Pval:
0.029

LSM1-4


Cluster:
Blue
Nodes:
62
Quality:
0.896
Pval:
0.000
Cluster:
Green
Nodes:
59
Quality:
0.851
Pval:
0.000
Cluster:
Red
Nodes:
21
Quality:
0.495
Pval:
0.004

POR1


Cluster:
Green
Nodes:
4
Quality:
0.712
Pval:
0.015
Cluster:
Red
Nodes:
5
Quality:
0.664
Pval:
0.011

STM1


Cluster:
Green
Nodes:
104
Quality:
0.789
Pval:
0.000
Cluster:
Red
Nodes:
10
Quality:
0.563
Pval:
0.003
Cluster:
Blue
Nodes:
43
Quality:
0.69
Pval:
0.000

TDH3


Cluster:
Green
Nodes:
10
Quality:
0.527
Pval:
0.013
Cluster:
Red
Nodes:
8
Quality:
0.564
Pval:
0.02

Basic information:

Nodes - Number of nodes in the cluster

Quality - The quality of the cluster, measured by the in-weight divided by the sum of the in-weight and the out-weight. A good cluster contains many heavyweight in-weights, and it is connected to the rest of the network only by a few lightweight edges.

P-value - The p-value of a one-sided Mann-Whitney U test performed on the in-weights and out-weights of the vertices. A low p-value means that it is more likely that the cluster is a valid finding and not the result of random fluctuations.

Visit ClustONE for detailed information.


Diagram legend



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