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miRTrace reveals the organismal origins of microRNA sequencing data
Stockholm University, Faculty of Science, Department of Molecular Biosciences, The Wenner-Gren Institute.
Stockholm University, Faculty of Science, Department of Molecular Biosciences, The Wenner-Gren Institute.
Stockholm University, Faculty of Science, Department of Molecular Biosciences, The Wenner-Gren Institute.
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Number of Authors: 62018 (English)In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 19, article id 213Article in journal (Refereed) Published
Abstract [en]

We present here miRTrace, the first algorithm to trace microRNA sequencing data back to their taxonomic origins. This is a challenge with profound implications for forensics, parasitology, food control, and research settings where cross-contamination can compromise results. miRTrace accurately (> 99%) assigns real and simulated data to 14 important animal and plant groups, sensitively detects parasitic infection in mammals, and discovers the primate origin of single cells. Applying our algorithm to over 700 public datasets, we find evidence that over 7% are cross-contaminated and present a novel solution to clean these computationally, even after sequencing has occurred.

Place, publisher, year, edition, pages
2018. Vol. 19, article id 213
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Environmental Biotechnology Biological Sciences
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URN: urn:nbn:se:su:diva-163552DOI: 10.1186/s13059-018-1588-9ISI: 000452319600001PubMedID: 30514392OAI: oai:DiVA.org:su-163552DiVA, id: diva2:1279327
Available from: 2019-01-16 Created: 2019-01-16 Last updated: 2019-01-16Bibliographically approved

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Kang, WenjingFromm, BastianBiryukova, InnaFriedländer, Marc R.
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