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$\rho$-index

A text index based on the suffixient suffix array sample. Basically a form of r-index [2] that can find MEMs [3], but:

  • smaller (hopefully), because the SA sample size probably significantly smaller
  • faster (hopefully), because it does not use backward stepping
  • less complex (subjectively)

Installation

TODO

Usage

TODO

Examples

TODO

Authors

Adrian Goga, Travis Gagie (original LCP), Nicola Prezza (suffixient).

License

MIT

References

[1] Ahmed, O., Baláž, A., Brown, N. K., Depuydt, L., Goga, A., Petescia, A., Zakeri, M., Fostier, J., Gagie, T., Langmead, B., Navarro, G. & Prezza, N. (2023). r-indexing without backward searching. arXiv preprint arXiv:2312.01359.

[2] Gagie, Travis, Gonzalo Navarro, and Nicola Prezza. "Optimal-time text indexing in BWT-runs bounded space." Proceedings of the Twenty-Ninth Annual ACM-SIAM Symposium on Discrete Algorithms. Society for Industrial and Applied Mathematics, 2018.

[3] Rossi, Massimiliano, et al. "MONI: a pangenomic index for finding maximal exact matches." Journal of Computational Biology 29.2 (2022): 169-187.