Fig. 4

Comparison of computational performance metrics for mutscan, Enrich2, and DiMSum. Generally, mutscan processes the included data sets faster and with a lower memory footprint than competing methods. In addition, only small amounts of data are being read from and written to disk during the processing. The digestFastqs() metrics for the Li_tRNA_sel30 data set are averaged across the five runs on the single input sample, since only one run is required for mutscan. Total I/O volumes are separated in input and output, indicated above by I and O, respectively. RSS, resident set size