德布鲁恩序列
德布鲁因图
计算机科学
图形
转录组
从头转录组组装
顺序装配
生物
软件
计算生物学
遗传学
理论计算机科学
基因表达
基因
组合数学
程序设计语言
数学
作者
Yu Peng,Henry C. M. Leung,Siu‐Ming Yiu,Mingju Lv,Xin‐Guang Zhu,Francis Y. L. Chin
出处
期刊:Bioinformatics
[Oxford University Press]
日期:2013-06-19
卷期号:29 (13): i326-i334
被引量:207
标识
DOI:10.1093/bioinformatics/btt219
摘要
Abstract Motivation: RNA sequencing based on next-generation sequencing technology is effective for analyzing transcriptomes. Like de novo genome assembly, de novo transcriptome assembly does not rely on any reference genome or additional annotation information, but is more difficult. In particular, isoforms can have very uneven expression levels (e.g. 1:100), which make it very difficult to identify low-expressed isoforms. One challenge is to remove erroneous vertices/edges with high multiplicity (produced by high-expressed isoforms) in the de Bruijn graph without removing correct ones with not-so-high multiplicity from low-expressed isoforms. Failing to do so will result in the loss of low-expressed isoforms or having complicated subgraphs with transcripts of different genes mixed together due to erroneous vertices/edges. Contributions: Unlike existing tools, which remove erroneous vertices/edges with multiplicities lower than a global threshold, we use a probabilistic progressive approach to iteratively remove them with local thresholds. This enables us to decompose the graph into disconnected components, each containing a few genes, if not a single gene, while retaining many correct vertices/edges of low-expressed isoforms. Combined with existing techniques, IDBA-Tran is able to assemble both high-expressed and low-expressed transcripts and outperform existing assemblers in terms of sensitivity and specificity for both simulated and real data. Availability: http://www.cs.hku.hk/∼alse/idba_tran. Contact: chin@cs.hku.hk Supplementary information: Supplementary data are available at Bioinformatics online.
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