HotSpot3D 
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HotSpot3D(Niu et al., 2016) is a suite of algorithms (https://github.com/ding-lab/hotspot3d) that identifies spatial mutation clusters on 3D protein structures. For this manuscript, we used version 1.4.1. For this study we used the following cutoffs: For intra-molecular clusters: 1) no linear amino-acid chain distance cutoff was enforced, 2) pairwise distances were calculated using the average amino-acid structure difference, 3) only mutation pairs with protein specific p-values less than 0.05, and 4) the maximum network radius was 10 Angstroms. For inter-molecular clusters: 1) no linear amino-acid chain distance cutoff was enforced, 2) pairwise distances were calculated using the average amino-acid structure difference, 3) only mutation pairs with protein specific p-values less than 0.05, and 4) the maximum network radius was 20 Angstroms. 

Input
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After pairwise distance preprocessing, we used recommended filters on mutations identified in the MC3 data file mc3.v0.2.8.PUBLIC.maf.gz (https://www.synapse.org/#!Synapse:syn7824274). 

Results
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Here we only provide information from significant clusters so all rows from these files were considered significant. Inter-molecular or clusters found on protein-protein interfaces are identified by a common cluster id in the info field.  Both the amino acid position of and the amino acid changes are included in comma separated values following “PROT_RANGE=” and “AMINOACIDS=”. 

Citation
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Niu, B., Scott, A.D., Sengupta, S., Bailey, M.H., Batra, P., Ning, J., Wyczalkowski, M.A., Liang, W.-W., Zhang, Q., and McLellan, M.D. (2016). Protein-structure-guided discovery of functional mutations across 19 cancer types. Nature genetics.

Contact
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Please contact either Amila Weerasinghe (amila AT wustl DOT edu) and Li Ding (lding AT wustl DOT edu) for more information.
