4 Search Results for "Paten, Benedict J."

Document
DOI: 10.4230/LIPIcs.WABI.2024.23
AlfaPang: Alignment Free Algorithm for Pangenome Graph Construction

Authors: Adam Cicherski, Anna Lisiecka, and Norbert Dojer

Published in: LIPIcs, Volume 312, 24th International Workshop on Algorithms in Bioinformatics (WABI 2024)

Abstract
The success of pangenome-based approaches to genomics analysis depends largely on the existence of efficient methods for constructing pangenome graphs that are applicable to large genome collections. In the current paper we present AlfaPang, a new pangenome graph building algorithm. AlfaPang is based on a novel alignment-free approach that allows to construct pangenome graphs using significantly less computational resources than state-of-the-art tools. The code of AlfaPang is freely available at https://github.com/AdamCicherski/AlfaPang.
Cite as

Adam Cicherski, Anna Lisiecka, and Norbert Dojer. AlfaPang: Alignment Free Algorithm for Pangenome Graph Construction. In 24th International Workshop on Algorithms in Bioinformatics (WABI 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 312, pp. 23:1-23:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{cicherski_et_al:LIPIcs.WABI.2024.23,
  author =	{Cicherski, Adam and Lisiecka, Anna and Dojer, Norbert},
  title =	{{AlfaPang: Alignment Free Algorithm for Pangenome Graph Construction}},
  booktitle =	{24th International Workshop on Algorithms in Bioinformatics (WABI 2024)},
  pages =	{23:1--23:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-340-9},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{312},
  editor =	{Pissis, Solon P. and Sung, Wing-Kin},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2024.23},
  URN =		{urn:nbn:de:0030-drops-206673},
  doi =		{10.4230/LIPIcs.WABI.2024.23},
  annote =	{Keywords: pangenome, variation graph, genome alignment, population genomics}
}
Document
DOI: 10.4230/LIPIcs.WABI.2024.17
A*PA2: Up to 19× Faster Exact Global Alignment

Authors: Ragnar Groot Koerkamp

Published in: LIPIcs, Volume 312, 24th International Workshop on Algorithms in Bioinformatics (WABI 2024)

Abstract
Motivation. Pairwise alignment is at the core of computational biology. Most commonly used exact methods are either based on O(ns) band doubling or O(n+s²) diagonal transition, where n is the sequence length and s the number of errors. However, as the length of sequences has grown, these exact methods are often replaced by approximate methods based on e.g. seed-and-extend and heuristics to bound the computed region. We would like to develop an exact method that matches the performance of these approximate methods. Recently, Astarix introduced the A* shortest path algorithm with the seed heuristic for exact sequence-to-graph alignment. A*PA adapted and improved this for pairwise sequence alignment and achieves near-linear runtime when divergence (error rate) is low, at the cost of being very slow when divergence is high. Methods. We introduce A*PA2, an exact global pairwise aligner with respect to edit distance. The goal of A*PA2 is to unify the near-linear runtime of A*PA on similar sequences with the efficiency of dynamic programming (DP) based methods. Like Edlib, A*PA2 uses Ukkonen’s band doubling in combination with Myers' bitpacking. A*PA2 1) uses large block sizes inspired by Block Aligner, 2) extends this with SIMD (single instruction, multiple data), 3) introduces a new profile for efficient computations, 4) introduces a new optimistic technique for traceback based on diagonal transition, 5) avoids recomputation of states where possible, and 6) applies the heuristics developed in A*PA and improves them using pre-pruning. Results. With the first 4 engineering optimizations, A*PA2-simple has complexity O(ns) and is 6× to 8× faster than Edlib for sequences ≥ 10 kbp. A*PA2-full also includes the heuristic and is often near-linear in practice for sequences with small divergence. The average runtime of A*PA2 is 19× faster than the exact aligners BiWFA and Edlib on >500 kbp long ONT (Oxford Nanopore Technologies) reads of a human genome having 6% divergence on average. On shorter ONT reads of 11% average divergence the speedup is 5.6× (avg. length 11 kbp) and 0.81× (avg. length 800 bp). On all tested datasets, A*PA2 is competitive with or faster than approximate methods.
Cite as

Ragnar Groot Koerkamp. A*PA2: Up to 19× Faster Exact Global Alignment. In 24th International Workshop on Algorithms in Bioinformatics (WABI 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 312, pp. 17:1-17:25, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{grootkoerkamp:LIPIcs.WABI.2024.17,
  author =	{Groot Koerkamp, Ragnar},
  title =	{{A*PA2: Up to 19× Faster Exact Global Alignment}},
  booktitle =	{24th International Workshop on Algorithms in Bioinformatics (WABI 2024)},
  pages =	{17:1--17:25},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-340-9},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{312},
  editor =	{Pissis, Solon P. and Sung, Wing-Kin},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2024.17},
  URN =		{urn:nbn:de:0030-drops-206610},
  doi =		{10.4230/LIPIcs.WABI.2024.17},
  annote =	{Keywords: Edit distance, Pairwise alignment, A*, Shortest path, Dynamic programming}
}
Document
DOI: 10.4230/LIPIcs.WABI.2018.4
Haplotype-aware graph indexes

Authors: Jouni Sirén, Erik Garrison, Adam M. Novak, Benedict J. Paten, and Richard Durbin

Published in: LIPIcs, Volume 113, 18th International Workshop on Algorithms in Bioinformatics (WABI 2018)

Abstract
The variation graph toolkit (VG) represents genetic variation as a graph. Each path in the graph is a potential haplotype, though most paths are unlikely recombinations of true haplotypes. We augment the VG model with haplotype information to identify which paths are more likely to be correct. For this purpose, we develop a scalable implementation of the graph extension of the positional Burrows-Wheeler transform. We demonstrate the scalability of the new implementation by indexing the 1000 Genomes Project haplotypes. We also develop an algorithm for simplifying variation graphs for k-mer indexing without losing any k-mers in the haplotypes.
Cite as

Jouni Sirén, Erik Garrison, Adam M. Novak, Benedict J. Paten, and Richard Durbin. Haplotype-aware graph indexes. In 18th International Workshop on Algorithms in Bioinformatics (WABI 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 113, pp. 4:1-4:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@InProceedings{siren_et_al:LIPIcs.WABI.2018.4,
  author =	{Sir\'{e}n, Jouni and Garrison, Erik and Novak, Adam M. and Paten, Benedict J. and Durbin, Richard},
  title =	{{Haplotype-aware graph indexes}},
  booktitle =	{18th International Workshop on Algorithms in Bioinformatics (WABI 2018)},
  pages =	{4:1--4:13},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-082-8},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{113},
  editor =	{Parida, Laxmi and Ukkonen, Esko},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2018.4},
  URN =		{urn:nbn:de:0030-drops-93060},
  doi =		{10.4230/LIPIcs.WABI.2018.4},
  annote =	{Keywords: FM-indexes, variation graphs, haplotypes}
}
Document
DOI: 10.4230/LIPIcs.WABI.2018.9
An Average-Case Sublinear Exact Li and Stephens Forward Algorithm

Authors: Yohei M. Rosen and Benedict J. Paten

Published in: LIPIcs, Volume 113, 18th International Workshop on Algorithms in Bioinformatics (WABI 2018)

Abstract
Hidden Markov models of haplotype inheritance such as the Li and Stephens model allow for computationally tractable probability calculations using the forward algorithms as long as the representative reference panel used in the model is sufficiently small. Specifically, the monoploid Li and Stephens model and its variants are linear in reference panel size unless heuristic approximations are used. However, sequencing projects numbering in the thousands to hundreds of thousands of individuals are underway, and others numbering in the millions are anticipated. To make the Li and Stephens forward algorithm for these datasets computationally tractable, we have created a numerically exact version of the algorithm with observed average case O(nk^{0.35}) runtime in number of genetic sites n and reference panel size k. This avoids any tradeoff between runtime and model complexity. We demonstrate that our approach also provides a succinct data structure for general purpose haplotype data storage. We discuss generalizations of our algorithmic techniques to other hidden Markov models.
Cite as

Yohei M. Rosen and Benedict J. Paten. An Average-Case Sublinear Exact Li and Stephens Forward Algorithm. In 18th International Workshop on Algorithms in Bioinformatics (WABI 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 113, pp. 9:1-9:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@InProceedings{rosen_et_al:LIPIcs.WABI.2018.9,
  author =	{Rosen, Yohei M. and Paten, Benedict J.},
  title =	{{An Average-Case Sublinear Exact Li and Stephens Forward Algorithm}},
  booktitle =	{18th International Workshop on Algorithms in Bioinformatics (WABI 2018)},
  pages =	{9:1--9:13},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-082-8},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{113},
  editor =	{Parida, Laxmi and Ukkonen, Esko},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2018.9},
  URN =		{urn:nbn:de:0030-drops-93116},
  doi =		{10.4230/LIPIcs.WABI.2018.9},
  annote =	{Keywords: Haplotype, Hidden Markov Model, Forward Algorithm, Lazy Evaluation}
}
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