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Seqenv: linking sequences to environments through text mining.

Lucas Sinclair1, Umer Z Ijaz2, Lars Juhl Jensen3

  • 1Department of Ecology and Genetics, Limnology, Uppsala University, Uppsala, Sweden.

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|December 29, 2016
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Summary
This summary is machine-generated.

Seqenv is a new software tool that analyzes microbial DNA sequences to determine their environmental origins. It helps connect isolated datasets, revealing patterns in microbial biogeography and environmental source tracking.

Keywords:
BioinformaticsEcologyGenomicsMicrobiologyOpen source softwarePipelineSequence analysisStatisticsText processing

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Area of Science:

  • Microbial Ecology
  • Bioinformatics
  • Environmental Science

Background:

  • Microbial ecology seeks to understand taxon distribution across environments.
  • High-throughput sequencing (HTS) generates vast, often isolated, microbial datasets.
  • Legacy sequence data with metadata can provide broader environmental context.

Purpose of the Study:

  • Introduce seqenv, a software tool for environmental context in HTS data.
  • Enable automated similarity searches and metadata extraction.
  • Link genetic information to specific environmental origins.

Main Methods:

  • Seqenv performs similarity searches against NCBI's 'nt' database.
  • It extracts textual metadata from search results.
  • A text mining algorithm links extracted terms to the Environmental Ontology (EnvO).

Main Results:

  • Seqenv determines environmental origins of individual sequences and taxa.
  • It summarizes complete samples by analyzing aggregated environmental data.
  • Demonstrated utility in ammonia-oxidizing archaea and Black Sea plankton datasets.

Conclusions:

  • Seqenv effectively places HTS data into a wider environmental context.
  • The tool reveals novel patterns in microbial biogeography.
  • Seqenv is valuable for environmental source tracking, paleontology, and microbial ecology studies.