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TopHat: discovering splice junctions with RNA-Seq

机译:TopHat:使用RNA-Seq发现剪接点

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摘要

>Motivation: A new protocol for sequencing the messenger RNA in a cell, known as RNA-Seq, generates millions of short sequence fragments in a single run. These fragments, or ‘reads’, can be used to measure levels of gene expression and to identify novel splice variants of genes. However, current software for aligning RNA-Seq data to a genome relies on known splice junctions and cannot identify novel ones. TopHat is an efficient read-mapping algorithm designed to align reads from an RNA-Seq experiment to a reference genome without relying on known splice sites.>Results: We mapped the RNA-Seq reads from a recent mammalian RNA-Seq experiment and recovered more than 72% of the splice junctions reported by the annotation-based software from that study, along with nearly 20 000 previously unreported junctions. The TopHat pipeline is much faster than previous systems, mapping nearly 2.2 million reads per CPU hour, which is sufficient to process an entire RNA-Seq experiment in less than a day on a standard desktop computer. We describe several challenges unique to ab initio splice site discovery from RNA-Seq reads that will require further algorithm development.>Availability: TopHat is free, open-source software available from >Contact: >Supplementary information: are available at Bioinformatics online.
机译:>动机:一种用于对信使RNA进行测序的新协议,称为RNA-Seq,可在一次运行中生成数百万个短序列片段。这些片段或“读段”可用于测量基因表达水平并鉴定基因的新型剪接变体。但是,当前用于将RNA-Seq数据与基因组比对的软件依赖于已知的剪接点,无法识别新的剪接点。 TopHat是一种高效的读取映射算法,旨在将RNA-Seq实验的读数与参考基因组对齐,而无需依赖已知的剪接位点。>结果:我们绘制了最近哺乳动物RNA的RNA-Seq读数-Seq实验,从该研究中恢复了基于注释的软件报告的超过72%的剪接连接点,以及近20000个以前未报告的连接点。 TopHat管道比以前的系统快得多,每CPU小时映射近220万次读取,这足以在不到一天的时间内在标准台式计算机上处​​理整个RNA-Seq实验。我们描述了RNA-Seq读取中从头开始剪接位点发现所面临的一些独特挑战,这些挑战需要进一步的算法开发。>可用性: TopHat是免费的开放源代码软件,可从>联系人: >补充信息:可在线访问生物信息学。

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