Table 2.
Comparison of pan genome applications using real S.typhi data (ERP001718)
| Samples | Software | Corea | Total | RAM (mb) | Wall time (s) |
|---|---|---|---|---|---|
| 8 | PGAP | 4545 | 4929 | 569 | 41 397 |
| PanOCT | 4544 | 4936 | 663 | 1457 | |
| LS-BSR | 4476 | 4816 | 270 | 2585 | |
| Roary | 4459 | 4871 | 156 | 44 | |
| 24 | PGAP | — | — | — | — |
| PanOCT | 4522 | 4991 | 5313 | 96 093 | |
| LS-BSR | 4451 | 4843 | 554 | 7807 | |
| Roary | 4436 | 4941 | 444 | 382 | |
| 1000 | PGAP | — | — | — | — |
| PanOCT | — | — | — | — | |
| LS-BSR | 4272 | 7265 | 17 413 | 345 019 | |
| Roary | 4016 | 9201 | 13 752 | 15 465 |
aCore is defined as a gene being in at least 99% of samples, which allows for some assembly errors in very large datasets. Where there are no results, the applications failed to complete within 5 days or used more than 60 GB of RAM. The first column is the number of unique S.typhi genomes in the input set with a mean of 54 contigs over all 1000 assemblies.