mirnaQC: a webserver for comparative quality control of miRNA-seq data
Metadatos
Mostrar el registro completo del ítemAutor
Aparicio Puerta, Ernesto; Gómez Martín, Cristina; Giannoukakos, Stavros Panagiotis; Medina Muñoz, José MaríaEditorial
Oxford University Press
Fecha
2020-06-02Referencia bibliográfica
Aparicio-Puerta, E., Gómez-Martín, C., Giannoukakos, S., Medina, J. M., Marchal, J. A., & Hackenberg, M. (2020). mirnaQC: a webserver for comparative quality control of miRNA-seq data. Nucleic Acids Research. [doi: 10.1093/nar/gkaa452]
Patrocinador
European Union (EU) 765492; Spanish Government AGL2017-88702-C2-2-R; Junta de Andalucia; European Union (EU) SOMM17-6109 UCE-PP2017-3; Instituto de Salud Carlos III, ERDF funds PIE16/00045; Instituto de Salud Carlos III IFI16/00041; Chair 'Doctors Galera-Requena in cancer stem cell research'; Excellence Research Unit "Modelling Nature" (MNat) SOMM17-6109Resumen
Although miRNA-seq is extensively used in many
different fields, its quality control is frequently restricted
to a PhredScore-based filter. Other important
quality related aspects like microRNA yield, the
fraction of putative degradation products (such as
rRNA fragments) or the percentage of adapter-dimers
are hard to assess using absolute thresholds. Here
we present mirnaQC, a webserver that relies on 34
quality parameters to assist in miRNA-seq quality
control. To improve their interpretability, quality attributes
are ranked using a reference distribution obtained
from over 36 000 publicly availablemiRNA-seq
datasets. Accepted input formats include FASTQ and
SRA accessions. The results page contains several
sections that deal with putative technical artefacts related
to library preparation, sequencing, contamination
or yield. Different visualisations, including PCA
and heatmaps, are available to help users identify
underlying issues. Finally, we show the usefulness
of this approach by analysing two publicly available
datasets and discussing the different quality issues
that can be detected using mirnaQC.