NURD: an implementation of a new method to estimate isoform expression from non-uniform RNA-seq data.
NURD: an implementation of a new method to estimate isoform expression from non-uniform RNA-seq data.
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DOI：
10.1186/1471-2105-14-220
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发表时间：
2013-07-10
影响因子：
3
通讯作者：
Zhang X
中科院分区：
文献类型：
--
作者：
Ma X;Zhang X
RNA-Seq技术在转录组研究中得到了广泛的应用，其中最重要的应用之一是估计基因及其选择性剪接异构体的表达水平。已经发表了几种算法来估计基于不同模型的表达式。最近，Wu等人发表了一种方法，通过使用非参数模型考虑位置相关的测序偏差，可以准确地估计异构体水平表达。该方法在处理不同的读分布时具有优势，但目前还没有一个有效的程序来实现该算法。我们在NURD程序中开发了一种有效的算法实现。它使用二进制区间搜索算法。该程序既可以纠正数据中测序偏差的全局趋势，也可以纠正每个基因特有的局部测序偏差。修正后的同型表达式估计在不同的读分布下更加可靠。该实现在内存成本和运行时间上都具有计算效率，并且可以很容易地扩展到大型数据集。NURD是估计异构体表达水平的有效、可靠的工具。根据reads映射结果和基因注释文件，NURD将输出表达式估计结果。该软件包可在http://bioinfo.au.tsinghua.edu.cn/software/NURD/免费用于学术用途。
RNA-Seq technology has been used widely in transcriptome study, and one of the most important applications is to estimate the expression level of genes and their alternative splicing isoforms. There have been several algorithms published to estimate the expression based on different models. Recently Wu et al. published a method that can accurately estimate isoform level expression by considering position-related sequencing biases using nonparametric models. The method has advantages in handling different read distributions, but there hasn’t been an efficient program to implement this algorithm. We developed an efficient implementation of the algorithm in the program NURD. It uses a binary interval search algorithm. The program can correct both the global tendency of sequencing bias in the data and local sequencing bias specific to each gene. The correction makes the isoform expression estimation more reliable under various read distributions. And the implementation is computationally efficient in both the memory cost and running time and can be readily scaled up for huge datasets. NURD is an efficient and reliable tool for estimating the isoform expression level. Given the reads mapping result and gene annotation file, NURD will output the expression estimation result. The package is freely available for academic use at http://bioinfo.au.tsinghua.edu.cn/software/NURD/.
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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
DOI：
10.1093/bioinformatics/btp692
发表时间：
2010-02-15
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Li B;Ruotti V;Stewart RM;Thomson JA;Dewey CN
通讯作者：
Dewey CN
影响因子：
12.3
作者：
Langmead B;Trapnell C;Pop M;Salzberg SL
通讯作者：
Salzberg SL
影响因子：
48
作者：
Mortazavi, Ali;Williams, Brian A.;Wold, Barbara
通讯作者：
Wold, Barbara
DOI：
10.1093/bioinformatics/btp120
发表时间：
2009-05-01
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Trapnell C;Pachter L;Salzberg SL
通讯作者：
Salzberg SL