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 available miRNA-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.

中文翻译：

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mirnaQC：用于比较质量控制miRNA-seq数据的网络服务器。

尽管miRNA-seq已广泛用于许多不同领域，但其质量控制通常仅限于基于PhredScore的过滤器。其他与质量相关的重要方面，例如microRNA产量，假定降解产物的比例（例如rRNA片段）或衔接子二聚体的百分比，很难使用绝对阈值进行评估。在这里，我们介绍mirnaQC，这是一个依靠34个质量参数来辅助miRNA-seq质量控制的网络服务器。为了提高其可解释性，使用从超过36000个可公开获得的miRNA-seq数据集中获得的参考分布对质量属性进行排名。可接受的输入格式包括FASTQ和SRA加入。结果页面包含多个部分，涉及与文库制备，测序，污染或产量相关的推定技术伪像。包括PCA和热图在内的各种可视化效果可用来帮助用户识别潜在问题。最后，我们通过分析两个公开可用的数据集并讨论可以使用mirnaQC检测到的不同质量问题，来展示这种方法的有用性。