PerM: efficient mapping of short sequencing reads with periodic full sensitive spaced seeds.
PerM: efficient mapping of short sequencing reads with periodic full sensitive spaced seeds.
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DOI：
10.1093/bioinformatics/btp486
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发表时间：
2009-10-01
期刊：
影响因子：
--
通讯作者：
Chen T
中科院分区：
文献类型：
--
作者：
Chen Y;Souaiaia T;Chen T
动机：下一代测序数据的爆炸式增长催生了新算法和软件工具的设计，以提供针对不同读取长度和测序技术的高效映射。特别是ABI的测序仪（SOLiD系统），由于其产生大量数据的能力以及将序列数据编码为彩色信号的独特策略，带来了巨大的计算挑战。结果如下：我们提出的映射软件，命名为PerM（周期性种子映射），使用周期性间隔种子显着提高映射效率为大型参考基因组相比，国家的最先进的程序。PerM中的数据结构只需要每个碱基4.5字节来索引人类基因组，允许整个基因组加载到内存中，而多个处理器同时将读取映射到参考。权重最大化的周期性种子对最多三个错配提供完全灵敏度，对四个和五个错配提供高灵敏度，同时最大限度地减少每个查询的随机命中数，显着加快运行时间。这样的灵敏度使得PerM成为SOLiD和Solexa读数的有价值的映射工具。可用性：http://code.google.com/p/perm/联系：tingchen@usc.edu补充信息：补充数据可在生物信息学在线。
Motivation: The explosion of next-generation sequencing data has spawned the design of new algorithms and software tools to provide efficient mapping for different read lengths and sequencing technologies. In particular, ABI's sequencer (SOLiD system) poses a big computational challenge with its capacity to produce very large amounts of data, and its unique strategy of encoding sequence data into color signals. Results: We present the mapping software, named PerM (Periodic Seed Mapping) that uses periodic spaced seeds to significantly improve mapping efficiency for large reference genomes when compared with state-of-the-art programs. The data structure in PerM requires only 4.5 bytes per base to index the human genome, allowing entire genomes to be loaded to memory, while multiple processors simultaneously map reads to the reference. Weight maximized periodic seeds offer full sensitivity for up to three mismatches and high sensitivity for four and five mismatches while minimizing the number random hits per query, significantly speeding up the running time. Such sensitivity makes PerM a valuable mapping tool for SOLiD and Solexa reads. Availability: http://code.google.com/p/perm/ Contact: tingchen@usc.edu Supplementary information: Supplementary data are available at Bioinformatics online.
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影响因子：
1.1
作者：
Nicolas, Francois;Rivals, Eric
通讯作者：
Rivals, Eric
DOI：
10.1109/tcbb.2005.12
发表时间：
2005-01-01
影响因子：
4.5
作者：
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通讯作者：
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DOI：
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发表时间：
2008-12-01
期刊：
Bioinformatics (Oxford, England)
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作者：
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通讯作者：
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影响因子：
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作者：
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通讯作者：
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影响因子：
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作者：
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