Table 2.
Running time (seconds) and memory usage (gigabytes) by Yanagi to generate segment library for fruit fly (BDGP6) and human (GRCh38) genomes, for both the preprocessing and segmentation steps
| BDGP6 | GRCh38 | ||||
|---|---|---|---|---|---|
| time(s) | memory(GB) | time(s) | memory(GB) | ||
| Preprocessing | 13 | 0.9 | 112 | 1.5 | |
| Segmentation | |||||
| L=40 | 20 | 0.4 | 248 | 1.3 | |
| L=108 | 20 | 0.4 | 250 | 1.3 | |
| L=1000 | 20 | 0.4 | 228 | 1.3 | |
| L=10000 | 8.5 | 0.4 | 77 | 1.3 | |
| Rapmap Indexing (4 Threads) | |||||
| L=108 | 103 | 0.8 | 420 | 2.6 | |
| Txs | 121 | 1.1 | 480 | 3.7 | |
| Rapmap Quantification (8 Threads) | |||||
| L=108 | 236 | 0.7 | 220 | 2.1 | |
| Txs | 292 | 1.2 | 416 | 3.1 | |
Time for the preprocessing step does not include the time to load the FASTA and GTF files. Most of the memory usage is from loading the input data in both steps. Running on a 6-core 2.1 GHz AMD processor, using single-threaded processes. The lower half shows the time and memory usage for running Rapmap’s quasi-mapping using the segments library and the the full transcriptome, to quantify samples of 40M paired-end reads, each of length 101bp.