Computing Strongly Connected Components in the Streaming Model

Laura, Luigi; Santaroni, Federico

doi:10.1007/978-3-642-19754-3_20

Cited by 6 publications

(2 citation statements)

References 21 publications

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“…The second observation is that in our problem, we never remove (arbitrary) nodes from the overlap graph. This simplifies data management as we can adopt tested data structures such as disjoint-set to identify connected components [14].…”

Section: Proposed Approachmentioning

confidence: 99%

“…For example, Isenburg and Shewcuk [11] adapted the union-find algorithm for a streaming 3D grid network to use in image processing, Agarwal et al considered I/O efficient solutions for terrain analysis [1], and Simsiri et al studied work-efficient parallel adaptations of union-find for incremental graph connectivity [29]. Laura and Santaroni introduced the first semi-streaming algorithm that makes a few passes to find strongly connected components in a directed graph [14]. These methods, however, are primarily focused on general streams where graph nodes and edges can be inserted or removed at any point of time.…”

Section: Related Workmentioning

confidence: 99%

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Identifying Taxonomic Units in Metagenomic DNA Streams

Zheng

Sarıyüce

Żola

2020

Preprint

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With the emergence of portable DNA sequencers, such as Oxford Nanopore Technology MinION, metagenomic DNA sequencing can be performed in real-time and directly in the field. However, because metagenomic DNA analysis is computationally and memory intensive, and the current methods are designed for batch processing, the current metagenomic tools are not well suited for mobile~devices. In this paper, we propose a new memory-efficient method to identify Operational Taxonomic Units (OTUs) in metagenomic DNA streams. Our method is based on finding connected components in overlap graphs constructed over a real-time stream of long DNA reads as produced by MinION platform. We propose an efficient algorithm to maintain connected components when an overlap graph is streamed, and show how redundant information can be removed from the stream by transitive closures. Through experiments on simulated and real-world metagenomic data, we demonstrate that the resulting solution is able to recover OTUs with high precision while remaining suitable for mobile computing devices.

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Section: Proposed Approachmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%