MiRTrace reveals the organismal origins of microRNA sequencing data

Wenjing Kang, Yrin Eldfjell, Bastian Fromm, Xavier P. Estivill, Inna Biryukova, Marc R. Friedländer

Research output: Contribution to journalArticle

3 Citations (Scopus)


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. miRTrace is freely available at https://github.com/friedlanderlab/mirtrace.

Original languageEnglish
Article number213
JournalGenome Biology
Issue number1
Publication statusPublished - 4 Dec 2018


ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Genetics
  • Cell Biology

Cite this

Kang, W., Eldfjell, Y., Fromm, B., Estivill, X. P., Biryukova, I., & Friedländer, M. R. (2018). MiRTrace reveals the organismal origins of microRNA sequencing data. Genome Biology, 19(1), [213]. https://doi.org/10.1186/s13059-018-1588-9