A haplotype-based normalization technique for the analysis and detection of allele specific expression.
A haplotype-based normalization technique for the analysis and detection of allele specific expression.
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DOI：
10.1186/s12859-016-1238-8
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发表时间：
2016-09-13
影响因子：
3
通讯作者：
Awadalla P
中科院分区：
文献类型：
--
作者：
Hodgkinson A;Grenier JC;Gbeha E;Awadalla P
等位基因特异性表达（ASE）已成为一种重要的表型，用于检测个人基因组中的顺式调节变化，胡说八道的介导的衰减和烙印，并已用于识别疾病基因座并考虑损害等位基因的渗透率。使用高通量技术检测ASE的检测依赖于对齐短阅读的测序数据，该过程具有固有的偏见，并且仍然需要开发快速，准确的方法来检测ASE，鉴于大数据项目中测序信息的前所未有的增长。
在这里，我们提出了一种新的方法，以使RNA测序数据归一化，以便在短时间内以高精度调用ASE事件。使用模拟数据集，我们发现我们的方法显着改善了杂合站点的参考等位基因量化与默认映射方法的参考等位基因量化，并且与现有ASE检测技术相比，相比操纵。最后，通过对Cartagene队列的96个良好型个体的外部和转录组进行测序，我们表征了跨个体的ASE水平，并发现基因组中ASE和吸烟中ASE的地点比例之间存在显着关联。
RNA测序数据的正确处理和分析对于控制映射偏见和检测正式ASE信号至关重要。通过在映射后标准化RNA测序信息，我们表明该方法可用于识别个人基因组中与生物学相关的信号。
本文的在线版本（DOI：10.1186/S12859-016-1238-8）包含补充材料，可供授权用户使用。
Allele specific expression (ASE) has become an important phenotype, being utilized for the detection of cis-regulatory variation, nonsense mediated decay and imprinting in the personal genome, and has been used to both identify disease loci and consider the penetrance of damaging alleles. The detection of ASE using high throughput technologies relies on aligning short-read sequencing data, a process that has inherent biases, and there is still a need to develop fast and accurate methods to detect ASE given the unprecedented growth of sequencing information in big data projects. Here, we present a new approach to normalize RNA sequencing data in order to call ASE events with high precision in a short time-frame. Using simulated datasets we find that our approach dramatically improves reference allele quantification at heterozygous sites versus default mapping methods and also performs well compared to existing techniques for ASE detection, such as filtering methods and mapping to parental genomes, without the need for complex and time consuming manipulation. Finally, by sequencing the exomes and transcriptomes of 96 well-phenotyped individuals of the CARTaGENE cohort, we characterise the levels of ASE across individuals and find a significant association between the proportion of sites undergoing ASE within the genome and smoking. The correct treatment and analysis of RNA sequencing data is vital to control for mapping biases and detect genuine ASE signals. By normalising RNA sequencing information after mapping, we show that this approach can be used to identify biologically relevant signals in personal genomes. The online version of this article (doi:10.1186/s12859-016-1238-8) contains supplementary material, which is available to authorized users.
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影响因子：
64.8
作者：
通讯作者：
--
DOI：
10.1126/science.1215040
发表时间：
2012-02-17
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
MacArthur DG;Balasubramanian S;Frankish A;Huang N;Morris J;Walter K;Jostins L;Habegger L;Pickrell JK;Montgomery SB;Albers CA;Zhang ZD;Conrad DF;Lunter G;Zheng H;Ayub Q;DePristo MA;Banks E;Hu M;Handsaker RE;Rosenfeld JA;Fromer M;Jin M;Mu XJ;Khurana E;Ye K;Kay M;Saunders GI;Suner MM;Hunt T;Barnes IH;Amid C;Carvalho-Silva DR;Bignell AH;Snow C;Yngvadottir B;Bumpstead S;Cooper DN;Xue Y;Romero IG;1000 Genomes Project Consortium;Wang J;Li Y;Gibbs RA;McCarroll SA;Dermitzakis ET;Pritchard JK;Barrett JC;Harrow J;Hurles ME;Gerstein MB;Tyler-Smith C
通讯作者：
Tyler-Smith C
RNA测序中的等位基因映射偏差不是EQTL研究中的主要混杂因素。
影响因子：
12.3
作者：
Panousis NI;Gutierrez-Arcelus M;Dermitzakis ET;Lappalainen T
通讯作者：
Lappalainen T
影响因子：
3.5
作者：
Heap GA;Yang JH;Downes K;Healy BC;Hunt KA;Bockett N;Franke L;Dubois PC;Mein CA;Dobson RJ;Albert TJ;Rodesch MJ;Clayton DG;Todd JA;van Heel DA;Plagnol V
通讯作者：
Plagnol V
影响因子：
11.2
作者：
Bosse, Yohan;Postma, Dirkje S.;Laviolette, Michel
通讯作者：
Laviolette, Michel