BMC Bioinformatics (Oct 2022)

Frugal alignment-free identification of FLT3-internal tandem duplications with FiLT3r

  • Augustin Boudry,
  • Sasha Darmon,
  • Nicolas Duployez,
  • Martin Figeac,
  • Sandrine Geffroy,
  • Maxime Bucci,
  • Karine Celli-Lebras,
  • Matthieu Duchmann,
  • Romane Joudinaud,
  • Laurène Fenwarth,
  • Olivier Nibourel,
  • Laure Goursaud,
  • Raphael Itzykson,
  • Hervé Dombret,
  • Mathilde Hunault,
  • Claude Preudhomme,
  • Mikaël Salson

DOI
https://doi.org/10.1186/s12859-022-04983-6
Journal volume & issue
Vol. 23, no. 1
pp. 1 – 16

Abstract

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Abstract Background Internal tandem duplications in the FLT3 gene, termed FLT3-ITDs, are useful molecular markers in acute myeloid leukemia (AML) for patient risk stratification and follow-up. FLT3-ITDs are increasingly screened through high-throughput sequencing (HTS) raising the need for robust and efficient algorithms. We developed a new algorithm, which performs no alignment and uses little resources, to identify and quantify FLT3-ITDs in HTS data. Results Our algorithm (FiLT3r) focuses on the k-mers from reads covering FLT3 exons 14 and 15. We show that those k-mers bring enough information to accurately detect, determine the length and quantify FLT3-ITD duplications. We compare the performances of FiLT3r to state-of-the-art alternatives and to fragment analysis, the gold standard method, on a cohort of 185 AML patients sequenced with capture-based HTS. On this dataset FiLT3r is more precise (no false positive nor false negative) than the other software evaluated. We also assess the software on public RNA-Seq data, which confirms the previous results and shows that FiLT3r requires little resources compared to other software. Conclusion FiLT3r is a free software available at https://gitlab.univ-lille.fr/filt3r/filt3r . The repository also contains a Snakefile to reproduce our experiments. We show that FiLT3r detects FLT3-ITDs better than other software while using less memory and time.

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