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This analysis implements a k-means clustering algorithm based on Bayesian Information Criterion BICC); we used a ∆BIC ≤2 to identify optimal numbers of clusters.
Due to the fact that the MotifSampler program [ 17], which was used in this analysis, implements a heuristic algorithm, the sampling results are very sensitive to the input parameters.
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This analysis implemented the statistical test of GO class abundance described above, using a significance threshold with a q-value ≤ 0.05 [ 85].
The pre-publication history for this paper can be accessed here: http://www.biomedcentral.com/1755-8794/7/8/prepub The preparation of this manuscript, data collection and processing, and the analysis implemented in this examination was supported by the National Institute of Health grants, U19 CA148112 R01 CA122443 R01 CA114343.
IL designed and conducted the analysis, implemented the algorithms and wrote the manuscript.
ZG developed the algorithm, performed the analysis, implemented the software and wrote the manuscript.
This analysis was implemented separately for channels in M1 and PMd.
To complement this analysis, we implemented secondary validation of MS/MS spectra associated with local single peptide hits using de novo peptide sequencing followed by MS-driven BLAST searching [30].
This analysis was implemented by using HelixTree software (see [ 23]).
This analysis was implemented using the DAMBE package [ 57].
This analysis was implemented in R using the rococo package (Bodenhofer and Klawonn, 2008).
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