Frugal alignment-free identification of FLT3-internal tandem duplications with FiLT3r.
Alignment-free
Cancer
High-throughput sequencing
Sequence analysis
Journal
BMC bioinformatics
ISSN: 1471-2105
Titre abrégé: BMC Bioinformatics
Pays: England
ID NLM: 100965194
Informations de publication
Date de publication:
28 Oct 2022
28 Oct 2022
Historique:
received:
02
06
2022
accepted:
07
10
2022
entrez:
28
10
2022
pubmed:
29
10
2022
medline:
2
11
2022
Statut:
epublish
Résumé
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. 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. 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.
Sections du résumé
BACKGROUND
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
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
CONCLUSIONS
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.
Identifiants
pubmed: 36307762
doi: 10.1186/s12859-022-04983-6
pii: 10.1186/s12859-022-04983-6
pmc: PMC9617311
doi:
Substances chimiques
fms-Like Tyrosine Kinase 3
EC 2.7.10.1
FLT3 protein, human
EC 2.7.10.1
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
448Subventions
Organisme : Institut National Du Cancer
ID : PHRC 2007/1911 and PRTK TRANSLA10-060
Commentaires et corrections
Type : ErratumIn
Informations de copyright
© 2022. The Author(s).
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