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Documents authored by Patro, Rob


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Patro, Rob

Document
Fast, Parallel, and Cache-Friendly Suffix Array Construction

Authors: Jamshed Khan, Tobias Rubel, Laxman Dhulipala, Erin Molloy, and Rob Patro

Published in: LIPIcs, Volume 273, 23rd International Workshop on Algorithms in Bioinformatics (WABI 2023)


Abstract
String indexes such as the suffix array (SA) and the closely related longest common prefix (LCP) array are fundamental objects in bioinformatics and have a wide variety of applications. Despite their importance in practice, few scalable parallel algorithms for constructing these are known, and the existing algorithms can be highly non-trivial to implement and parallelize. In this paper we present CaPS-SA, a simple and scalable parallel algorithm for constructing these string indexes inspired by samplesort. Due to its design, CaPS-SA has excellent memory-locality and thus incurs fewer cache misses and achieves strong performance on modern multicore systems with deep cache hierarchies. We show that despite its simple design, CaPS-SA outperforms existing state-of-the-art parallel SA and LCP-array construction algorithms on modern hardware. Finally, motivated by applications in modern aligners where the query strings have bounded lengths, we introduce the notion of a bounded-context SA and show that CaPS-SA can easily be extended to exploit this structure to obtain further speedups.

Cite as

Jamshed Khan, Tobias Rubel, Laxman Dhulipala, Erin Molloy, and Rob Patro. Fast, Parallel, and Cache-Friendly Suffix Array Construction. In 23rd International Workshop on Algorithms in Bioinformatics (WABI 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 273, pp. 16:1-16:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)


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@InProceedings{khan_et_al:LIPIcs.WABI.2023.16,
  author =	{Khan, Jamshed and Rubel, Tobias and Dhulipala, Laxman and Molloy, Erin and Patro, Rob},
  title =	{{Fast, Parallel, and Cache-Friendly Suffix Array Construction}},
  booktitle =	{23rd International Workshop on Algorithms in Bioinformatics (WABI 2023)},
  pages =	{16:1--16:21},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-294-5},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{273},
  editor =	{Belazzougui, Djamal and Ouangraoua, A\"{i}da},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2023.16},
  URN =		{urn:nbn:de:0030-drops-186424},
  doi =		{10.4230/LIPIcs.WABI.2023.16},
  annote =	{Keywords: Suffix Array, Longest Common Prefix, Data Structures, Indexing, Parallel Algorithms}
}
Document
Fulgor: A Fast and Compact {k-mer} Index for Large-Scale Matching and Color Queries

Authors: Jason Fan, Noor Pratap Singh, Jamshed Khan, Giulio Ermanno Pibiri, and Rob Patro

Published in: LIPIcs, Volume 273, 23rd International Workshop on Algorithms in Bioinformatics (WABI 2023)


Abstract
The problem of sequence identification or matching - determining the subset of reference sequences from a given collection that are likely to contain a short, queried nucleotide sequence - is relevant for many important tasks in Computational Biology, such as metagenomics and pan-genome analysis. Due to the complex nature of such analyses and the large scale of the reference collections a resource-efficient solution to this problem is of utmost importance. This poses the threefold challenge of representing the reference collection with a data structure that is efficient to query, has light memory usage, and scales well to large collections. To solve this problem, we describe how recent advancements in associative, order-preserving, k-mer dictionaries can be combined with a compressed inverted index to implement a fast and compact colored de Bruijn graph data structure. This index takes full advantage of the fact that unitigs in the colored de Bruijn graph are monochromatic (all k-mers in a unitig have the same set of references of origin, or "color"), leveraging the order-preserving property of its dictionary. In fact, k-mers are kept in unitig order by the dictionary, thereby allowing for the encoding of the map from k-mers to their inverted lists in as little as 1+o(1) bits per unitig. Hence, one inverted list per unitig is stored in the index with almost no space/time overhead. By combining this property with simple but effective compression methods for inverted lists, the index achieves very small space. We implement these methods in a tool called Fulgor. Compared to Themisto, the prior state of the art, Fulgor indexes a heterogeneous collection of 30,691 bacterial genomes in 3.8× less space, a collection of 150,000 Salmonella enterica genomes in approximately 2× less space, is at least twice as fast for color queries, and is 2-6 × faster to construct.

Cite as

Jason Fan, Noor Pratap Singh, Jamshed Khan, Giulio Ermanno Pibiri, and Rob Patro. Fulgor: A Fast and Compact {k-mer} Index for Large-Scale Matching and Color Queries. In 23rd International Workshop on Algorithms in Bioinformatics (WABI 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 273, pp. 18:1-18:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)


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@InProceedings{fan_et_al:LIPIcs.WABI.2023.18,
  author =	{Fan, Jason and Singh, Noor Pratap and Khan, Jamshed and Pibiri, Giulio Ermanno and Patro, Rob},
  title =	{{Fulgor: A Fast and Compact \{k-mer\} Index for Large-Scale Matching and Color Queries}},
  booktitle =	{23rd International Workshop on Algorithms in Bioinformatics (WABI 2023)},
  pages =	{18:1--18:21},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-294-5},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{273},
  editor =	{Belazzougui, Djamal and Ouangraoua, A\"{i}da},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2023.18},
  URN =		{urn:nbn:de:0030-drops-186446},
  doi =		{10.4230/LIPIcs.WABI.2023.18},
  annote =	{Keywords: k-mers, Colored de Bruijn Graph, Compression, Read-mapping}
}
Document
Perplexity: Evaluating Transcript Abundance Estimation in the Absence of Ground Truth

Authors: Jason Fan, Skylar Chan, and Rob Patro

Published in: LIPIcs, Volume 201, 21st International Workshop on Algorithms in Bioinformatics (WABI 2021)


Abstract
There has been rapid development of probabilistic models and inference methods for transcript abundance estimation from RNA-seq data. These models aim to accurately estimate transcript-level abundances, to account for different biases in the measurement process, and even to assess uncertainty in resulting estimates that can be propagated to subsequent analyses. The assumed accuracy of the estimates inferred by such methods underpin gene expression based analysis routinely carried out in the lab. Although hyperparameter selection is known to affect the distributions of inferred abundances (e.g. producing smooth versus sparse estimates), strategies for performing model selection in experimental data have been addressed informally at best. Thus, we derive perplexity for evaluating abundance estimates on fragment sets directly. We adapt perplexity from the analogous metric used to evaluate language and topic models and extend the metric to carefully account for corner cases unique to RNA-seq. In experimental data, estimates with the best perplexity also best correlate with qPCR measurements. In simulated data, perplexity is well behaved and concordant with genome-wide measurements against ground truth and differential expression analysis. To our knowledge, our study is the first to make possible model selection for transcript abundance estimation on experimental data in the absence of ground truth.

Cite as

Jason Fan, Skylar Chan, and Rob Patro. Perplexity: Evaluating Transcript Abundance Estimation in the Absence of Ground Truth. In 21st International Workshop on Algorithms in Bioinformatics (WABI 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 201, pp. 4:1-4:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)


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@InProceedings{fan_et_al:LIPIcs.WABI.2021.4,
  author =	{Fan, Jason and Chan, Skylar and Patro, Rob},
  title =	{{Perplexity: Evaluating Transcript Abundance Estimation in the Absence of Ground Truth}},
  booktitle =	{21st International Workshop on Algorithms in Bioinformatics (WABI 2021)},
  pages =	{4:1--4:22},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-200-6},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{201},
  editor =	{Carbone, Alessandra and El-Kebir, Mohammed},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2021.4},
  URN =		{urn:nbn:de:0030-drops-143578},
  doi =		{10.4230/LIPIcs.WABI.2021.4},
  annote =	{Keywords: RNA-seq, transcript abundance estimation, model selection}
}
Document
Rainbowfish: A Succinct Colored de Bruijn Graph Representation

Authors: Fatemeh Almodaresi, Prashant Pandey, and Rob Patro

Published in: LIPIcs, Volume 88, 17th International Workshop on Algorithms in Bioinformatics (WABI 2017)


Abstract
The colored de Bruijn graph— a variant of the de Bruijn graph which associates each edge (i.e., k-mer) with some set of colors - is an increasingly important combinatorial structure in computational biology. Iqbal et al. demonstrated the utility of this structure for representing and assembling a collection (population) of genomes, and showed how it can be used to accurately detect genetic variants. Muggli et al. introduced VARI, a representation of the colored de Bruijn graph that adopts the BOSS representation for the de Bruijn graph topology and achieves considerable savings in space over Cortex, albeit with some sacrifice in speed. The memory-efficient representation of VARI allows the colored de Bruijn graph to be constructed and analyzed for large datasets, beyond what is possible with Cortex. In this paper, we introduce Rainbowfish, a succinct representation of the color information of the colored de Bruijn graph that reduces the space usage even further. Our representation also uses BOSS to represent the de Bruijn graph, but decomposes the color sets based on an equivalence relation and exploits the inherent skewness in the distribution of these color sets. The Rainbowfish representation is compressed based on the 0th-order entropy of the color sets, which can lead to a significant reduction in the space required to store the relevant information for each edge. In practice, Rainbowfish achieves up to a 20x improvement in space over VARI. Rainbowfish is written in C++11 and is available at https://github.com/COMBINE-lab/rainbowfish.

Cite as

Fatemeh Almodaresi, Prashant Pandey, and Rob Patro. Rainbowfish: A Succinct Colored de Bruijn Graph Representation. In 17th International Workshop on Algorithms in Bioinformatics (WABI 2017). Leibniz International Proceedings in Informatics (LIPIcs), Volume 88, pp. 18:1-18:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)


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@InProceedings{almodaresi_et_al:LIPIcs.WABI.2017.18,
  author =	{Almodaresi, Fatemeh and Pandey, Prashant and Patro, Rob},
  title =	{{Rainbowfish: A Succinct Colored de Bruijn Graph Representation}},
  booktitle =	{17th International Workshop on Algorithms in Bioinformatics (WABI 2017)},
  pages =	{18:1--18:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-050-7},
  ISSN =	{1868-8969},
  year =	{2017},
  volume =	{88},
  editor =	{Schwartz, Russell and Reinert, Knut},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2017.18},
  URN =		{urn:nbn:de:0030-drops-76576},
  doi =		{10.4230/LIPIcs.WABI.2017.18},
  annote =	{Keywords: de Bruijn graph, succinct data structures, rank and select operation, colored de Bruijn graph}
}

Patro, Robert

Document
Salient Frame Detection for Molecular Dynamics Simulations

Authors: Youngmin Kim, Robert Patro, Cheuk Yiu Ip, Dianne P. O’Leary, and Andriy Anishkin

Published in: Dagstuhl Follow-Ups, Volume 2, Scientific Visualization: Interactions, Features, Metaphors (2011)


Abstract
Recent advances in sophisticated computational techniques have facilitated simulation of incrediblydetailed time-varying trajectories and in the process have generated vast quantities of simulation data. The current tools to analyze and comprehend large-scale time-varying data, however, lag far behind our ability to produce such simulation data. Saliency-based analysis can be applied to time-varying 3D datasets for the purpose of summarization, abstraction, and motion analysis. As the sizes of time-varying datasets continue to grow, it becomes more and more difficult to comprehend vast amounts of data and information in a short period of time. In this paper, we use eigenanalysis to generate orthogonal basis functions over sliding windows to characterize regions of unusual deviations and significant trends. Our results show that motion subspaces provide an effective technique for summarization of large molecular dynamics trajectories.

Cite as

Youngmin Kim, Robert Patro, Cheuk Yiu Ip, Dianne P. O’Leary, and Andriy Anishkin. Salient Frame Detection for Molecular Dynamics Simulations. In Scientific Visualization: Interactions, Features, Metaphors. Dagstuhl Follow-Ups, Volume 2, pp. 160-175, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2011)


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@InCollection{kim_et_al:DFU.Vol2.SciViz.2011.160,
  author =	{Kim, Youngmin and Patro, Robert and Yiu Ip, Cheuk and O’Leary, Dianne P. and Anishkin, Andriy},
  title =	{{Salient Frame Detection for Molecular Dynamics Simulations}},
  booktitle =	{Scientific Visualization: Interactions, Features, Metaphors},
  pages =	{160--175},
  series =	{Dagstuhl Follow-Ups},
  ISBN =	{978-3-939897-26-2},
  ISSN =	{1868-8977},
  year =	{2011},
  volume =	{2},
  editor =	{Hagen, Hans},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DFU.Vol2.SciViz.2011.160},
  URN =		{urn:nbn:de:0030-drops-32926},
  doi =		{10.4230/DFU.Vol2.SciViz.2011.160},
  annote =	{Keywords: Saliency based analysis, Molecular Dynamics, Simulation}
}
Document
Saliency Guided Summarization of Molecular Dynamics Simulations

Authors: Robert Patro, Cheuk Yiu Ip, and Amitabh Varshney

Published in: Dagstuhl Follow-Ups, Volume 1, Scientific Visualization: Advanced Concepts (2010)


Abstract
We present a novel method to measure saliency in molecular dynamics simulation data. This saliency measure is based on a multiscale center-surround mechanism, which is fast and efficient to compute. We explore the use of the saliency function to guide the selection of representative and anomalous timesteps for summarization of simulations. To this end, we also introduce a multiscale keyframe selection procedure which automatically provides keyframes representing the simulation at varying levels of coarseness. We compare our saliency guided keyframe approach against other methods, and show that it consistently selects superior keyframes as measured by their predictive power in reconstructing the simulation.

Cite as

Robert Patro, Cheuk Yiu Ip, and Amitabh Varshney. Saliency Guided Summarization of Molecular Dynamics Simulations. In Scientific Visualization: Advanced Concepts. Dagstuhl Follow-Ups, Volume 1, pp. 321-335, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2010)


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@InCollection{patro_et_al:DFU.SciViz.2010.321,
  author =	{Patro, Robert and Ip, Cheuk Yiu and Varshney, Amitabh},
  title =	{{Saliency Guided Summarization of Molecular Dynamics Simulations}},
  booktitle =	{Scientific Visualization: Advanced Concepts},
  pages =	{321--335},
  series =	{Dagstuhl Follow-Ups},
  ISBN =	{978-3-939897-19-4},
  ISSN =	{1868-8977},
  year =	{2010},
  volume =	{1},
  editor =	{Hagen, Hans},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DFU.SciViz.2010.321},
  URN =		{urn:nbn:de:0030-drops-27134},
  doi =		{10.4230/DFU.SciViz.2010.321},
  annote =	{Keywords: Molecuar Dynamics, Saliency, Simulation}
}
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