Extract from the HC–plot of Gavin2006 showing subsets of interest (SOIs).

<p>The green square frames the SOI of the three POL complexes. Black represents that two proteins are never in the same cluster, dark blue colors represent clusters with a low co-occurrence and bright colors represent clusters with a high co-occurrence.</p

Hierarchical cluster plots for two different HC4N parameter settings on the Gavin2006-SOI dataset.

<p>The numbers at the labels (_1,_2,_3,_12,_123) show the POL-cluster assignments according to cyc2008. <b>Left</b>: Too–strict parameter settings (co-occurrence threshold 0.25, completeness threshold 0.4): The clusters are scattered and show low overlap. It is not clear which proteins are shared by how many complexes. <b>Right</b>: Lower parameters (0.2 and 0.5). The green frames show the three POL complexes as the HC4N result. The red square shows a characteristic pattern of four highly co-occurring proteins that in addition, partly co-occur with most other proteins (yellow frames). They are the shared proteins of the three complexes.</p

Hierarchical cluster plots for the Malovannaya SOI.

<p><b>Left</b>: With too–strict automatic thresholds (co-occurrence 0.09, completeness 0.6), correct clusters are visible but not the connections between them. <b>Right</b>: Lower parameters (0.05 and 0.5) create patterns indicating shared proteins. Two large and two small clusters are visible, framed by the thick green squares. MED appears as a separate cluster, while INT and POL appear together as dense subsets of one cluster. POL and INT can build a more stable complex together than POL and MED. One pattern (framed in yellow) contains POLR2 A/B/C/G, which are important interactors within both the POL-INT and the POL-MED complex. ELL2 and SPEN (framed in cyan) comprise another pattern and are important for the interaction between MLLT and the MED complex.</p

Accuracy of HC4N in comparison to competing methods.

<p>The values for CACHET [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0139704#pone.0139704.ref017" target="_blank">17</a>] and Cai et al. [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0139704#pone.0139704.ref018" target="_blank">18</a>] were taken from the respective publications. We applied the other methods on all datasets. “NA” means that no value for this dataset was available in the corresponding original publication. “NP” means that we tried the method on the dataset but it was not possible to produce a result.</p><p>Accuracy of HC4N in comparison to competing methods.</p

General overview of the HC4N strategy.

<p>The IP/MS dataset is analyzed with 4N to create the clusters of level 1. The dataset is split up into subsets where each subset contains all proteins from a level–1 cluster. 4N is applied to each of the subsets to create level 2. The procedure is repeated to create levels 3 and above, until no further splits are possible.</p

IP/MS datasets used for the analyses.

<p>IP/MS datasets used for the analyses.</p

Network representation of the Gavin2006-SOI HC4N result.

<p>The green ovals indicate the three POL complexes as found by HC4N. The forth oval (gray) contains proteins that are known to interact with POL but were not in the cyc2008 reference. The protein name suffixes (_1,_2,_3,_12,_123) indicate the assignment to POLI-POLIII from the reference. The four shared proteins from the characteristic pattern (framed in dark gray) occur in all complexes and together multiple times.</p

Example HC4N result tree.

<p>For clarity, the co-occurrence is displayed in each node. Clusters with many proteins of low co-occurrence and with large child nodes indicate interacting complexes at the highest interaction level. Complexes built of several cores have a higher co-occurrence and leafs as child nodes. Leaf nodes with a high co-occurrence symbolize complex cores. Leaf nodes with low co-occurrence mostly do not represent complex cores, and their interpretation is not always univocal.</p

Summarized results of HC4N on all tested datasets.

<p>Summarized results of HC4N on all tested datasets.</p

Example hierarchical cluster plots for different co-occurrence thresholds at HC4N level 1.

<p>The plots are small cutouts from the analysis of the Krogan2004 dataset. Left: The threshold is set too low with 0.125. Randomly co-occurring proteins lead to large, highly overlapping clusters, which do not represent protein complexes. At a higher threshold of 0.35, the clusters overlap less, and possible complexes and cores are visible. At a too–high threshold of 0.6, the clusters represent mostly complex cores, and their relation to each other is not visible. HC4N sets the set–wise completeness threshold automatically to 0.64 in all three examples.</p