RNA2HLA: HLA-based quality control of RNA-seq datasets.
RNA2HLA: HLA-based quality control of RNA-seq datasets.
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DOI：
10.1093/bib/bbab055
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发表时间：
2021-09-02
影响因子：
9.5
通讯作者：
O'Connor D
中科院分区：
文献类型：
--
作者：
Chelysheva I;Pollard AJ;O'Connor D
RNA测序（RNA-seq）是生物医学研究中广泛使用的获取转录组的方法。研究经常包括在不同时间点或不同条件下从同一个体采集的多个样本，将这些样本正确分配给每个特定参与者显然非常重要。在这里，我们建议利用人类白细胞抗原（HLA）复合物的高度多态性基因分型，以验证RNA-seq样本对个体的正确分配。我们介绍了RNA 2 HLA，这是一种新的质量控制（QC）工具，用于对RNA-seq数据进行研究范围内的HLA分型，从而识别来自共同来源的样本。RNA 2 HLA允许基于其HLA类型对RNA样本进行精确分配和分组。引人注目的是，RNA 2 HLA揭示了来自公开数据集的错误分配样本，从而证明了该工具对RNA-seq研究质量控制的重要性。此外，我们的工具成功地以四位分辨率提取了HLA等位基因，并可用于从基于RNA-seq的研究中进行大规模HLA分型，这将服务于样本QC之外的多种研究目的。
RNA-sequencing (RNA-seq) is a widely used approach for accessing the transcriptome in biomedical research. Studies frequently include multiple samples taken from the same individual at various time points or under different conditions, correct assignment of those samples to each particular participant is evidently of great importance. Here, we propose taking advantage of typing the highly polymorphic genes from the human leukocyte antigen (HLA) complex in order to verify the correct allocation of RNA-seq samples to individuals. We introduce RNA2HLA, a novel quality control (QC) tool for performing study-wide HLA-typing for RNA-seq data and thereby identifying the samples from the common source. RNA2HLA allows precise allocation and grouping of RNA samples based on their HLA types. Strikingly, RNA2HLA revealed wrongly assigned samples from publicly available datasets and thereby demonstrated the importance of this tool for the quality control of RNA-seq studies. In addition, our tool successfully extracts HLA alleles in four-digital resolution and can be used to perform massive HLA-typing from RNA-seq based studies, which will serve multiple research purposes beyond sample QC.
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影响因子：
9.5
作者：
Chelysheva I;Pollard AJ;O'Connor D
通讯作者：
O'Connor D
影响因子：
14.9
作者：
Robinson, James;Barker, Dominic J.;Marsh, Steven G. E.
通讯作者：
Marsh, Steven G. E.
影响因子：
8.8
作者：
Rechtien A;Richert L;Lorenzo H;Martrus G;Hejblum B;Dahlke C;Kasonta R;Zinser M;Stubbe H;Matschl U;Lohse A;Krähling V;Eickmann M;Becker S;VEBCON Consortium;Thiébaut R;Altfeld M;Addo MM
通讯作者：
Addo MM
影响因子：
12.3
作者：
Huang Y;Yang J;Ying D;Zhang Y;Shotelersuk V;Hirankarn N;Sham PC;Lau YL;Yang W
通讯作者：
Yang W
影响因子：
3
作者：
Ka S;Lee S;Hong J;Cho Y;Sung J;Kim HN;Kim HL;Jung J
通讯作者：
Jung J