Using pseudoalignment and base quality to accurately quantify microbial community composition
Table 3
Computational requirements and speed of Karp, Kallisto, SINTAX, UCLUST, USEARCH61, SortMeRNA, and the Wang et al. (2007) Naive Bayes using Mothur.
All programs were run using 12 multi-threaded cores except Mothur. Mothur’s memory requirements scale with the number of cores used, and in order to keep memory <16GB we limited it to 4 cores. The values for UCLUST and USEARCH give the time to assign taxonomy, generally with these methods reads are clustered before taxonomy is assigned and the value in parenthesis gives the time to first cluster and then assign taxonomy. The results for the method 16S Classifier are not shown: it was fast and required a few minutes at most; however its memory usage scaled dramatically with the number of reads. To keep memory usage < 128GB samples needed to be split into several smaller samples and then reassembled. Additionally, it could not be run in parallel, so a meaningful comparison against the other methods of speed and memory requirements was not possible.