| Literature DB >> 27933096 |
Timo Beller1, Enno Ohlebusch1.
Abstract
[This corrects the article DOI: 10.1186/s13015-016-0083-7.].Entities:
Year: 2016 PMID: 27933096 PMCID: PMC5126863 DOI: 10.1186/s13015-016-0090-8
Source DB: PubMed Journal: Algorithms Mol Biol ISSN: 1748-7188 Impact factor: 1.405
Breakdown of the space usage of the variants of Algorithm A4
| Algorithm | Part | 62 | 7 × Chr1 | 7 × HG |
|---|---|---|---|---|
| A4 | wt-bwt | 0.42 (23.83%) | 0.44 (36.23%) | 0.43 (22.68%) |
| A4 | Nodes | 0.10 (5.94%) | 0.03 (2.61%) | 0.04 (2.02%) |
| A4 |
| 0.16 (8.93%) | 0.16 (12.86%) | 0.16 (8.25%) |
| A4 |
| 0.14 (8.04%) | 0.14 (11.57%) | 0.14 (7.42%) |
| A4 | wt-doc | 0.93 (53.26%) | 0.45 (36.73%) | 1.13 (59.63%) |
| A4compr1 | wt-bwt | 0.42 (28.57%) | 0.44 (47.83%) | 0.43 (26.85%) |
| A4compr1 | Nodes | 0.10 (7.12%) | 0.03 (3.44%) | 0.04 (2.39%) |
| A4compr1 |
| 0.00 (0.23%) | 0.00 (0.12%) | 0.00 (0.09%) |
| A4compr1 |
| 0.00 (0.23%) | 0.00 (0.12%) | 0.00 (0.08%) |
| A4compr1 | wt-doc | 0.93 (63.85%) | 0.45 (48.49%) | 1.13 (70.59%) |
| A4compr2 | wt-bwt | 0.16 (13.03%) | 0.22 (31.01%) | 0.22 (15.62%) |
| A4compr2 | Nodes | 0.10 (8.67%) | 0.03 (4.55%) | 0.04 (2.76%) |
| A4compr2 |
| 0.00 (0.28%) | 0.00 (0.16%) | 0.00 (0.10%) |
| A4compr2 |
| 0.00 (0.28%) | 0.00 (0.16%) | 0.00 (0.10%) |
| A4compr2 | wt-doc | 0.93 (77.74%) | 0.45 (64.11%) | 1.13 (81.42%) |
The first column shows the algorithm used in the experiment (the k-mer size is 50). The second column specifies the different data structures used: wt-bwt stands for the wavelet tree of the (including rank and select support), nodes stands for the array of nodes (the implicit graph representation), and are the bit vectors described in “Computation of right-maximal k-mers and node identifiers” section (including rank support), and wt-doc stands for the wavelet tree of the document array. The remaining columns show the memory usage in bytes per base pair and, in parentheses, their percentage