Intron-centric estimation of alternative splicing from RNA-seq data.
Intron-centric estimation of alternative splicing from RNA-seq data.
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DOI：
10.1093/bioinformatics/bts678
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发表时间：
2013-01-15
期刊：
影响因子：
--
通讯作者：
Guigó R
中科院分区：
文献类型：
--
作者：
Pervouchine DD;Knowles DG;Guigó R
动机：新技术带来了前所未有的高通量测序数据，同时也带来了分析和解释方面的巨大挑战。剪接百分比(PSI)指标估计单个外显子跳过事件的发生率，可以通过计算与已知或预测的剪接连接对齐的读数来直接计算。然而，大多数人类剪接事件比单外显子跳跃更复杂。结果：在这份简短的报告中，我们提出了一个框架，将该指标推广到任意类别的剪接事件。我们将以外显子为中心的观点改为以内含子为中心的观点，将的值分为两个指数，并分别测量内含子5‘端和3’端的剪接率。有两个不同指数的好处是，它们使剪接反应的两个不同的基本动作解卷。对剪接索引的完备性进行了类似的分解。该框架被实现为bam2ssj，这是一个BAM文件处理管道，用于对对齐到剪接点或与剪接点重叠的读取进行特定于链的计数。它可以用作量化来自RNA-SEQ数据的剪接连接的一致协议，因为目前还不存在这样的标准程序。提供：bam2ssj的C代码是开源的，可通过https://github.com/pervouchine/bam2ssj联系：dp@crg.eu获得
Motivation: Novel technologies brought in unprecedented amounts of high-throughput sequencing data along with great challenges in their analysis and interpretation. The percent-spliced-in (PSI, ) metric estimates the incidence of single-exon–skipping events and can be computed directly by counting reads that align to known or predicted splice junctions. However, the majority of human splicing events are more complex than single-exon skipping. Results: In this short report, we present a framework that generalizes the metric to arbitrary classes of splicing events. We change the view from exon centric to intron centric and split the value of into two indices, and , measuring the rate of splicing at the 5′ and 3′ end of the intron, respectively. The advantage of having two separate indices is that they deconvolute two distinct elementary acts of the splicing reaction. The completeness of splicing index is decomposed in a similar way. This framework is implemented as bam2ssj, a BAM-file–processing pipeline for strand-specific counting of reads that align to splice junctions or overlap with splice sites. It can be used as a consistent protocol for quantifying splice junctions from RNA-seq data because no such standard procedure currently exists. Availability: The C code of bam2ssj is open source and is available at https://github.com/pervouchine/bam2ssj Contact: dp@crg.eu
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影响因子：
48
作者：
Katz, Yarden;Wang, Eric T.;Airoldi, Edoardo M.;Burge, Christopher B.
通讯作者：
Burge, Christopher B.
影响因子：
64.8
作者：
通讯作者：
--
影响因子：
14.8
作者：
通讯作者：
--
影响因子：
7
作者：
Tilgner H;Knowles DG;Johnson R;Davis CA;Chakrabortty S;Djebali S;Curado J;Snyder M;Gingeras TR;Guigó R
通讯作者：
Guigó R
DOI：
10.1093/bioinformatics/btp352
发表时间：
2009-08-15
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Li H;Handsaker B;Wysoker A;Fennell T;Ruan J;Homer N;Marth G;Abecasis G;Durbin R;1000 Genome Project Data Processing Subgroup
通讯作者：
1000 Genome Project Data Processing Subgroup