Evaluation and comparison of computational tools for RNA-seq isoform quantification.
Evaluation and comparison of computational tools for RNA-seq isoform quantification.
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DOI：
10.1186/s12864-017-4002-1
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发表时间：
2017-08-07
期刊：
影响因子：
4.4
通讯作者：
Zhao S
中科院分区：
文献类型：
--
作者：
Zhang C;Zhang B;Lin LL;Zhao S
在高等真核生物中通常观察到选择性剪接的转录异构体。这些亚型的表达水平是理解健康组织中正常功能和疾病状态进展的关键。然而，由于例如有限的读取长度和深度测序的成本，在转录物水平上的表达的准确定量受到当前RNA-seq技术的限制。已经开发了大量的工具来解决这个问题，我们使用实验和模拟RNA-seq数据集对这些工具进行了全面的评估。我们发现，最近开发的免维护工具既快速又准确。所有方法的准确性主要受基因结构复杂性的影响，在解释短转录本的定量结果时必须谨慎。使用TP 53基因模拟，我们发现测序深度和不同异构体的相对丰度都会影响定量准确性。我们的综合评估有助于数据分析人员在选择异构体定量的计算工具时做出明智的选择。本文的在线版本（doi：10.1186/s12864-017-4002-1）包含补充材料，可供授权用户使用。
Alternatively spliced transcript isoforms are commonly observed in higher eukaryotes. The expression levels of these isoforms are key for understanding normal functions in healthy tissues and the progression of disease states. However, accurate quantification of expression at the transcript level is limited with current RNA-seq technologies because of, for example, limited read length and the cost of deep sequencing. A large number of tools have been developed to tackle this problem, and we performed a comprehensive evaluation of these tools using both experimental and simulated RNA-seq datasets. We found that recently developed alignment-free tools are both fast and accurate. The accuracy of all methods was mainly influenced by the complexity of gene structures and caution must be taken when interpreting quantification results for short transcripts. Using TP53 gene simulation, we discovered that both sequencing depth and the relative abundance of different isoforms affect quantification accuracy Our comprehensive evaluation helps data analysts to make informed choice when selecting computational tools for isoform quantification. The online version of this article (doi:10.1186/s12864-017-4002-1) 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
影响因子：
46.9
作者：
Patro, Rob;Mount, Stephen M.;Kingsford, Carl
通讯作者：
Kingsford, Carl
影响因子：
46.9
作者：
Trapnell C;Williams BA;Pertea G;Mortazavi A;Kwan G;van Baren MJ;Salzberg SL;Wold BJ;Pachter L
通讯作者：
Pachter L
影响因子：
7
作者：
Harrow J;Frankish A;Gonzalez JM;Tapanari E;Diekhans M;Kokocinski F;Aken BL;Barrell D;Zadissa A;Searle S;Barnes I;Bignell A;Boychenko V;Hunt T;Kay M;Mukherjee G;Rajan J;Despacio-Reyes G;Saunders G;Steward C;Harte R;Lin M;Howald C;Tanzer A;Derrien T;Chrast J;Walters N;Balasubramanian S;Pei B;Tress M;Rodriguez JM;Ezkurdia I;van Baren J;Brent M;Haussler D;Kellis M;Valencia A;Reymond A;Gerstein M;Guigó R;Hubbard TJ
通讯作者：
Hubbard TJ
影响因子：
12.3
作者：
Kanitz A;Gypas F;Gruber AJ;Gruber AR;Martin G;Zavolan M
通讯作者：
Zavolan M