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. 2020 Jan 20;48(4):e23. doi: 10.1093/nar/gkz1209

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© The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research.

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

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Figure 8. — MOG performance benchmarks. MOG was benchmarked using the entire Hu-cancer-RNASeq-dataset (18 212 genes over 7142 samples), and using chunks of this dataset.(A) Comparison of MOG to R-based (PIVOT). Dataset size was limited to the amount of data that could be loaded in PIVOT (410 samples). % processor time (% CPU utilization) was calculated over 30 min; theoretical maximum value = total processors in computer x 100 (400 in this case). (B) Execution times for computing differentially expressed genes using Mann–Whitney U test. Red dots, MOG; blue dot, PIVOT (410 samples). Inset, expanded scale to display MOG execution times. (C) MOG execution times for pairwise computations of Pearson correlation of a gene (BIRC5) with all other genes in the datasets. (Other tools cannot perform this computation). Execution times are linear with data size; full dataset analysis took 16 s.