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FACEPAI: a script for fast and consistent environmental DNA processing and identification
Stockholm University, Faculty of Science, Department of Zoology. Swedish Museum of Natural History, Sweden.
2019 (English)In: BMC Ecology, ISSN 1472-6785, E-ISSN 1472-6785, Vol. 19, no 1, article id 51Article in journal (Refereed) Published
Abstract [en]

Background

The use of environmental DNA (eDNA) has become an increasing important tool in environmental surveys and taxonomic research. High throughput sequencing of samples from soil, water, sediment, trap alcohol or bulk samples generate large amount of barcode sequences that can be assigned to a known taxon with a reference sequence. This process can however be bioinformatic cumbersome and time consuming, especially for researchers without specialised bioinformatic training. A number of different software packages and pipelines are available, but require training in preparation of data, running of analysis and formatting results. Comparison of results produced by different packages are often difficult.

Results

FACEPIE is an open source script dependant on a few open source applications that provides a pipeline for rapid analysis and taxonomic assignment of environmental DNA samples. It requires an initial formatting of a reference database, using the script CaPReSe, and a configuration file and can thereafter be run to process any number of samples in succession using the same settings and references. Both configuration and executing are designed to demand as little hands on work as possible, while assuring repeatable results.

Conclusion

The demonstration using example data from real environmental samples provides results in a time span ranging from less than 3 min to just above 15 min depending on the numbers of sequences to process. The memory usage is below 2 GB on a desktop PC. FACEPAI and CaPReSe provides a pipeline for analysing a large number of eDNA samples on common equipment, with little bioinformatic skills necessary, for subsequent ecological and taxonomical studies.

Place, publisher, year, edition, pages
2019. Vol. 19, no 1, article id 51
National Category
Bioinformatics and Systems Biology
Identifiers
URN: urn:nbn:se:su:diva-176488DOI: 10.1186/s12898-019-0269-1ISI: 000501166600001OAI: oai:DiVA.org:su-176488DiVA, id: diva2:1376492
Funder
The Swedish Taxonomy Initiative (ArtDatabanken, SLU), dha 2014-149 4.3Available from: 2019-12-09 Created: 2019-12-09 Last updated: 2020-01-07Bibliographically approved

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