TABLE 2.
Performance comparison between SSRMMD and other software programs for identifying genome-wide SSR feature loci.
| Software | Thread | Rice (Zhenshan97, ∼0.39 Gb) |
Cotton (TM1, ∼2.29 Gb) |
Wheat (CS, ∼14.23 Gb) |
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| Number | Time (m:s) | Mem (Mb) | Number | Time (m:s) | Mem (Mb) | Number | Time (m:s) | Mem (Mb) | ||
| SSRIT | 1 | 111,960 | 5:53 | 131.55 | 384,488 | 34:45 | 343.04 | 1,345,128 | 210:47 | 2,503.85 |
| MISA | 1 | 111,905 | 5:50 | 205.52 | 384,400 | 35:31 | 382.60 | 1,343,830 | 212:45 | 4,195.61 |
| GMATAa | 1 | 111,905 | 7:28 | 85.48 | 384,400 | 42:15 | 361.72 | 1,343,831 | 254:46 | 1,739.50 |
| PERF | 1 | 111,960 | 8:49 | 211.60 | 384,488 | 52:32 | 522.91 | 1,345,128 | 320:36 | 3,325.42 |
| Kmer-SSR | 1 | 111,960 | 14:08 | 123.05 | 384,488 | 83:14 | 169.00 | 1,345,128 | 516:19 | 1,028.44 |
| Kmer-SSR | 12 | 111,960 | 5:28 | 321.95 | 384,488 | 28:20 | 353.96 | 1,345,128 | 205:19 | 1,251.40 |
| SSRMMD | 1 | 111,960 | 4:49 | 139.38 | 384,488 | 28:36 | 421.95 | 1,345,128 | 175:19 | 2,404.68 |
| SSRMMD | 6 | 111,960 | 1:08 | 466.19 | 384,488 | 6:46 | 1,044.88 | 1,345,128 | 43:40 | 5,972.30 |
| SSRMMD | 12 | 111,960 | 0:49 | 731.02 | 384,488 | 4:28 | 1,717.92 | 1,345,128 | 27:05 | 11,248.89 |
Note. SSRMMD, Simple Sequence Repeat Molecular Marker Developer; SSR, simple sequence repeat. aBecause GMATA and Kmer-SSR could not simultaneously mine different types of motifs in one task, these two programs were multiply performed to identify SSRs, then the time was added, and memory peak was selected as the maximum among all tasks.