Sparse Binary Relation Representations for Genome Graph Annotation Article Swipe
Mikhail Karasikov
,
Harun Mustafa
,
Amir Joudaki
,
Sara Javadzadeh
,
Gunnar Rätsch
,
André Kahles
·
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.1101/468512
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.1101/468512
High-throughput DNA sequencing data is accumulating in public repositories, and efficient approaches for storing and indexing such data are in high demand. In recent research, several graph data structures have been proposed to represent large sets of sequencing data and to allow for efficient querying of sequences. In particular, the concept of labeled de Bruijn graphs has been explored by several groups. While there has been good progress towards representing the sequence graph in small space, methods for storing a set of labels on top of such graphs are still not sufficiently explored. It is also currently not clear how characteristics of the input data, such as the sparsity and correlations of labels, can help to inform the choice of method to compress the graph labeling. In this work, we present a new compression approach, Multi-BRWT , which is adaptive to different kinds of input data. We show an up to 29% improvement in compression performance over the basic BRWT method, and up to a 68% improvement over the current state-of-the-art for de Bruijn graph label compression. To put our results into perspective, we present a systematic analysis of five different state-of-the-art annotation compression schemes, evaluate key metrics on both artificial and real-world data and discuss how different data characteristics influence the compression performance. We show that the improvements of our new method can be robustly reproduced for different representative real-world datasets.
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- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1101/468512
- https://www.biorxiv.org/content/biorxiv/early/2019/01/25/468512.full.pdf
- OA Status
- green
- Cited By
- 4
- References
- 33
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2900124800
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2900124800Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1101/468512Digital Object Identifier
- Title
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Sparse Binary Relation Representations for Genome Graph AnnotationWork title
- Type
-
preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2018Year of publication
- Publication date
-
2018-11-12Full publication date if available
- Authors
-
Mikhail Karasikov, Harun Mustafa, Amir Joudaki, Sara Javadzadeh, Gunnar Rätsch, André KahlesList of authors in order
- Landing page
-
https://doi.org/10.1101/468512Publisher landing page
- PDF URL
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https://www.biorxiv.org/content/biorxiv/early/2019/01/25/468512.full.pdfDirect link to full text PDF
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
- OA URL
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https://www.biorxiv.org/content/biorxiv/early/2019/01/25/468512.full.pdfDirect OA link when available
- Concepts
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De Bruijn graph, Computer science, Graph, Search engine indexing, Theoretical computer science, Data compression, Data mining, Artificial intelligenceTop concepts (fields/topics) attached by OpenAlex
- Cited by
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4Total citation count in OpenAlex
- Citations by year (recent)
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2023: 1, 2020: 1, 2019: 1, 2017: 1Per-year citation counts (last 5 years)
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33Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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