TY - JOUR
T1 - mirnaQC
T2 - A webserver for comparative quality control of miRNA-seq data
AU - Aparicio-Puerta, Ernesto
AU - Gomez-Martin, Cristina
AU - Giannoukakos, Stavros
AU - Maria Medina, Jose
AU - Marchal, Juan Antonio
AU - Hackenberg, Michael
N1 - Funding Information: This work was supported by European Union [765492]; Spanish Government [AGL2017-88702-C2-2-R] to M.H.; Consejería de Economía, Conocimiento, Empresas y Uni-versidad de la Junta de Andalucía and European Regional Development Funds (ERDF) [SOMM17-6109, UCE-PP2017-3] to J.A.M. and M.H.; Instituto de Salud Carlos III, ERDF funds [PIE16/00045] to J.A.M.; Chair ‘Doctors Galera-Requena in cancer stem cell research’ (to J.A.M.); Instituto de Salud Carlos III [IFI16/00041] to E.A. Funding for open access charges: Excellence Research Unit “Modelling Nature” (MNat) [SOMM17-6109]. Conflict of interest statement. None declared. Publisher Copyright: © 2020 Oxford University Press. All rights reserved.
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85087320268&partnerID=8YFLogxK
U2 - https://doi.org/10.1093/NAR/GKAA452
DO - https://doi.org/10.1093/NAR/GKAA452
M3 - Article
C2 - 32484556
SN - 0305-1048
VL - 48
SP - W262-W267
JO - Nucleic Acids Research
JF - Nucleic Acids Research
IS - W1
ER -