Projecten per jaar
Uittreksel
The widespread use of High-Throughput Sequencing (HTS) for detection of plant viruses
and sequencing of plant virus genomes has led to the generation of large amounts of data
and of bioinformatics challenges to process them. Many bioinformatics pipelines for virus
detection are available, making the choice of a suitable one difficult. A robust
benchmarking is needed for the unbiased comparison of the pipelines, but there is
currently a lack of reference datasets that could be used for this purpose. We present 7
semi-artificial datasets composed of real RNA-seq datasets from virus-infected plants
spiked with artificial virus reads. Each dataset addresses challenges that could prevent virus
detection. We also present 3 real datasets showing a challenging virus composition as well
as 8 completely artificial datasets to test haplotype reconstruction software. With these
datasets that address several diagnostic challenges, we hope to encourage virologists,
diagnosticians and bioinformaticians to evaluate and benchmark their pipeline(s).
and sequencing of plant virus genomes has led to the generation of large amounts of data
and of bioinformatics challenges to process them. Many bioinformatics pipelines for virus
detection are available, making the choice of a suitable one difficult. A robust
benchmarking is needed for the unbiased comparison of the pipelines, but there is
currently a lack of reference datasets that could be used for this purpose. We present 7
semi-artificial datasets composed of real RNA-seq datasets from virus-infected plants
spiked with artificial virus reads. Each dataset addresses challenges that could prevent virus
detection. We also present 3 real datasets showing a challenging virus composition as well
as 8 completely artificial datasets to test haplotype reconstruction software. With these
datasets that address several diagnostic challenges, we hope to encourage virologists,
diagnosticians and bioinformaticians to evaluate and benchmark their pipeline(s).
| Oorspronkelijke taal | Engels |
|---|---|
| Artikel nummer | e53 |
| Tijdschrift | Peer community Journal |
| Volume | 1 |
| Exemplaarnummer | 1 |
| Pagina's (van-tot) | 1-15 |
| Aantal pagina’s | 15 |
| ISSN | 2804-3871 |
| DOI's | |
| Publicatiestatus | Gepubliceerd - 2-dec.-2021 |
Projecten
- 2 Afgerond
-
VIRVRIJUIT: Evaluatie en optimalisatie van een high-throughput sequencing (HTS) gebaseerde strategie voor de detectie van virussen en bacteriën, in functie van de certificering en in vitro therapie voor het creëren van virusvrije moederplanten
De Jonghe, K. (Projectverantwoordelijke), Dhooghe, E. (Voormalig Projectbegeleider), Dewitte, I. (Onderzoeker), Guldentops, E. (Voormalig doctoraatsstudent) & Ommeslag, S. (Projectmedewerker)
1/09/21 → 31/08/25
Project: Onderzoek
-
PHBN : Plantengezondheid bioinformatica netwerk
Haegeman, A. (Onderzoeker), Van Laecke, K. (Projectverantwoordelijke), De Jonghe, K. (Onderzoeker) & Schaumont, D. (Voormalig Onderzoeker)
1/09/19 → 28/02/22
Project: Onderzoek
Datasets
-
Semi-artificial datasets as a resource for validation of bioinformatics pipelines for plant virus detection
Tamisier, L. (Bijdrager), Haegeman, A. (Bijdrager), Foucart, Y. (Bijdrager), Fouillien, N. (Bijdrager), Al Rwahnih, M. (Bijdrager), Buzkan, N. (Bijdrager), Candresse, T. (Bijdrager), Chiumenti, M. (Bijdrager), De Jonghe, K. (Bijdrager), Lefebvre, M. (Bijdrager), Margaria, P. (Bijdrager), Reynard, J. S. (Bijdrager), Stevens, K. (Bijdrager), Kutnjak, D. (Bijdrager) & Massart, S. (Bijdrager), Dryad, 1-jan.-2021
DOI: 10.5061/dryad.0zpc866z8, http://datadryad.org/stash/dataset/doi:10.5061/dryad.0zpc866z8 en nog één link, https://zenodo.org/records/5642357 (minder tonen)
Dataset