Assessing characteristics of RNA amplification methods for single cell RNA sequencing.
Assessing characteristics of RNA amplification methods for single cell RNA sequencing.
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DOI：
10.1186/s12864-016-3300-3
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发表时间：
2016-11-24
期刊：
影响因子：
4.4
通讯作者：
Kim J
中科院分区：
文献类型：
--
作者：
Dueck HR;Ai R;Camarena A;Ding B;Dominguez R;Evgrafov OV;Fan JB;Fisher SA;Herstein JS;Kim TK;Kim JM;Lin MY;Liu R;Mack WJ;McGroty S;Nguyen JD;Salathia N;Shallcross J;Souaiaia T;Spaethling JM;Walker CP;Wang J;Wang K;Wang W;Wildberg A;Zheng L;Chow RH;Eberwine J;Knowles JA;Zhang K;Kim J
最近，单细胞分辨率的RNA测量产生了令人惊讶的见解。单细胞RNA测序（scRNA-seq）方法已经受到了相当大的关注，但单细胞方法的广泛可靠性和控制其性能的因素仍然知之甚少。在此，我们进行了大规模的对照实验，以评估三种scRNA-seq方法的传递函数和调节功能的因素。所有三种方法检测到的基因数量都大于预期数量的70%，并且检测到丰度大于2到4个分子的基因的概率为50%。尽管分子数量少，但测序深度显著影响基因检测。虽然不同方法在检测和定量上的偏差在质量上相似，但偏差的程度不同，与分子方案的差异一致。所有方法的测量可靠性随着表达水平的增加而增加，我们保守地估计，当表达水平大于~ 5-10个分子时，测量结果是定量的。基于这些广泛的对照研究，我们提出单细胞rna测序已经成熟，可以获得定量的生物学信息。本文的在线版本（doi:10.1186/s12864-016-3300-3）包含补充材料，可供授权用户使用。
Recently, measurement of RNA at single cell resolution has yielded surprising insights. Methods for single-cell RNA sequencing (scRNA-seq) have received considerable attention, but the broad reliability of single cell methods and the factors governing their performance are still poorly known. Here, we conducted a large-scale control experiment to assess the transfer function of three scRNA-seq methods and factors modulating the function. All three methods detected greater than 70% of the expected number of genes and had a 50% probability of detecting genes with abundance greater than 2 to 4 molecules. Despite the small number of molecules, sequencing depth significantly affected gene detection. While biases in detection and quantification were qualitatively similar across methods, the degree of bias differed, consistent with differences in molecular protocol. Measurement reliability increased with expression level for all methods and we conservatively estimate measurements to be quantitative at an expression level greater than ~5–10 molecules. Based on these extensive control studies, we propose that RNA-seq of single cells has come of age, yielding quantitative biological information. The online version of this article (doi:10.1186/s12864-016-3300-3) contains supplementary material, which is available to authorized users.
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DOI：
10.1093/bioinformatics/btu638
发表时间：
2015-01-15
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Anders S;Pyl PT;Huber W
通讯作者：
Huber W
DOI：
10.1126/science.1247651
发表时间：
2014-02-14
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Jaitin DA;Kenigsberg E;Keren-Shaul H;Elefant N;Paul F;Zaretsky I;Mildner A;Cohen N;Jung S;Tanay A;Amit I
通讯作者：
Amit I
影响因子：
3.7
作者：
Derrien T;Estellé J;Marco Sola S;Knowles DG;Raineri E;Guigó R;Ribeca P
通讯作者：
Ribeca P
影响因子：
12.3
作者：
Gentleman RC;Carey VJ;Bates DM;Bolstad B;Dettling M;Dudoit S;Ellis B;Gautier L;Ge Y;Gentry J;Hornik K;Hothorn T;Huber W;Iacus S;Irizarry R;Leisch F;Li C;Maechler M;Rossini AJ;Sawitzki G;Smith C;Smyth G;Tierney L;Yang JY;Zhang J
通讯作者：
Zhang J
影响因子：
12.3
作者：
Langmead B;Trapnell C;Pop M;Salzberg SL
通讯作者：
Salzberg SL