Automated Querying of Genome Databases

Schattner, Peter

doi:10.1371/journal.pcbi.0030001

Cited by 18 publications

(6 citation statements)

References 20 publications

(21 reference statements)

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“…Sequencing of genomes is advancing rapidly but deciphering the complex layers of information they contain is a challenging, long-term endeavour [58, 59]. Genomes are not only inherently complex, they also exhibit remarkable dynamism, with phenomena such as recombination, transposition and horizontal gene transfer contributing to the creation of genomic ‘churn’ that makes feature distribution difficult to map [60]. These issues, combined with rapid data accumulation, coverage limitations, and assembly errors – make generation of complete and accurate annotations difficult [62, 63].…”

Section: Discussionmentioning

confidence: 99%

“…However, it can be challenging to implement efficiently. Automated pipelines are generally required to implement large-scale screens [60], and these can produce copious output data that are difficult to manage and interpret without an appropriate analytical framework. In this report, we introduce DIGS – a robust analytical platform for conducting large-scale in silico screens – and describe an open software framework (the DIGS tool) for implementing it.…”

Section: Discussionmentioning

confidence: 99%

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A novel approach to exploring the dark genome and its application to mapping of the vertebrate virus ‘fossil record’

Blanco-Melo,

Campbell,

Zhu

et al. 2023

Preprint

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Background: Genomic regions that remain poorly understood, often referred to as the "dark genome," contain a variety of functionally relevant and biologically informative genome features. These include endogenous viral elements (EVEs) - virus-derived sequences that can dramatically impact host biology and serve as a virus "fossil record". In this study, we introduce a database-integrated genome screening (DIGS) approach to investigating the dark genome in silico, focusing on EVEs found within vertebrate genomes. Results: Using DIGS on 874 vertebrate species genomes, we uncovered approximately 1.1 million EVE sequences, with over 99% originating from endogenous retroviruses or transposable elements that contain EVE DNA. We show that the remaining 6038 sequences represent over a thousand distinct horizontal gene transfer events across ten virus families, including some that have not previously been reported as EVEs. We explore the genomic and phylogenetic characteristics of non-retroviral EVEs and determine their rates of acquisition during vertebrate evolution. Our study uncovers novel virus diversity and broadens our knowledge of virus distribution among vertebrate hosts. It also provides new insights into the long-term evolution of highly pathogenic filoviruses. Conclusions: We comprehensively catalogue and analyse EVEs within 874 vertebrate genomes, shedding light on the distribution, diversity and long-term evolution of viruses, and revealing their extensive impact on vertebrate genome evolution. Our results demonstrate the power of linking a relational database management system to a similarity search-based screening pipeline for in silico exploration of the dark genome.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

A novel approach to exploring the dark genome and its application to mapping of the vertebrate virus ‘fossil record’

Blanco-Melo,

Campbell,

Zhu

et al. 2023

Preprint

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“…Besides a web-based genome browser [2], the database is programmatically accessible through three interfaces: the official command-line tools and libraries [3,4], the Distributed Annotation System (DAS) [5] server, and direct access to a public MySQL database server. UCSC’s official tools consist of command-line executables and API libraries written in the C language.…”

Section: Introductionmentioning

confidence: 99%

The Ruby UCSC API: accessing the UCSC genome database using Ruby

et al. 2012

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BackgroundThe University of California, Santa Cruz (UCSC) genome database is among the most used sources of genomic annotation in human and other organisms. The database offers an excellent web-based graphical user interface (the UCSC genome browser) and several means for programmatic queries. A simple application programming interface (API) in a scripting language aimed at the biologist was however not yet available. Here, we present the Ruby UCSC API, a library to access the UCSC genome database using Ruby.ResultsThe API is designed as a BioRuby plug-in and built on the ActiveRecord 3 framework for the object-relational mapping, making writing SQL statements unnecessary. The current version of the API supports databases of all organisms in the UCSC genome database including human, mammals, vertebrates, deuterostomes, insects, nematodes, and yeast.The API uses the bin index—if available—when querying for genomic intervals. The API also supports genomic sequence queries using locally downloaded *.2bit files that are not stored in the official MySQL database. The API is implemented in pure Ruby and is therefore available in different environments and with different Ruby interpreters (including JRuby).ConclusionsAssisted by the straightforward object-oriented design of Ruby and ActiveRecord, the Ruby UCSC API will facilitate biologists to query the UCSC genome database programmatically. The API is available through the RubyGem system. Source code and documentation are available at https://github.com/misshie/bioruby-ucsc-api/ under the Ruby license. Feedback and help is provided via the website at http://rubyucscapi.userecho.com/.

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“…The power of the bioinformatics approach has been increased still further with the seamless integration with a statistical package such as R/Bioconductor (19). Recent reports that have utilized these tools (20,21) have provided a comprehensive approach concerning functionality by providing technical details. The present mini-review takes a different tack, examining these genome data mining tools from the user's perspective and surveying their real world applications.…”

Section: Introductionmentioning

confidence: 99%

Genome data mining for everyone

Lee

Kim²

2008

BMB Reports

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The genomic sequences of a huge number of species have been determined. Typically, these genome sequences and the associated annotation data are accessed through Internet-based genome browsers that offer a user-friendly interface. Intelligent use of the data should expedite biological knowledge discovery. Such activity is collectively called data mining and involves queries that can be simple, complex, and even combinational. Various tools have been developed to make genome data mining available to computational and experimental biologists alike. In this mini-review, some tools that have proven successful will be introduced along with examples taken from published reports. [BMB reports 2008; 41(11): 757-764]

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Automated Querying of Genome Databases

Cited by 18 publications

References 20 publications

A novel approach to exploring the dark genome and its application to mapping of the vertebrate virus ‘fossil record’

A novel approach to exploring the dark genome and its application to mapping of the vertebrate virus ‘fossil record’

The Ruby UCSC API: accessing the UCSC genome database using Ruby

Genome data mining for everyone

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