高通量DNA测序数据的生物信息学方法

doi:10.11959/j.issn.2096-0271.2016021

Abstract

Abstract:

DNA sequence data generated by high-throughput sequencing technology is short in length, and the amount of data is enormous. The challenges and opportunities of the big data in high-throughput sequencing environment were analyzed. The data compression, the assembly of metagenomic sequence data, and algorithms and tools of metagenomic sequence data analysis also were summarized and discussed. Finally, the future of the study on short read DNA sequence data in high-throughput sequencing environment was discussed.

Key words: high-throughput DNA sequencing, bioinformatics, short read sequence data compression, short read sequence data splicing, short read sequence data analysis

CLC Number:

TP399

xiaojuan Zhan,dengju Yao,huaiqiu Zhu. Bioinformatics methods for high-throughput DNA sequencing data[J]. Big Data Research, 2016, 2(2): 76-87.

Figures/Tables 4

References 56

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项目名称	成员	年度
DNA元件百科全书（ENCODE）计划^[6]	400个科学家分成32组	2003
癌症和肿瘤基因图谱（TCGA）计划^[7]	超过150个研究人员，12个基金会	2005
千人基因组计划^[8]	1 000个基因组项目财团	2007
人类微生物组计划（HMP）^[9]	美国、日本、中国等10多个国家参与	2007
万种脊椎动物基因组联盟（G10K）^[10]	研究10 000种脊椎动物序列群落的科学家	2009
自闭症测序联盟（ASC）^[11]	超过20个独立的研究小组	2010
人类肠道宏基因组计划（MetaHIT）^[12]	来自中国、美国、丹麦、法国、日本、西班牙、英国、芬兰8个国家的学术界和工业界的13家研究机构	2010
人类蛋白质组计划（HPP）^[13]	中国、美国、德国、英国、加拿大、日本、韩国、澳大利亚、法国、俄国等19个国家（地区）	2010
地球微生物组计划（EMP）^[14]	国际交叉学科联盟	2011
5 000种昆虫和其他节肢动物基因组计划^[15]	国际交叉学科联盟	2011
国际癌症基因组联盟（ICGC）^[16]	联合各国科学家对癌症基因组开展研究	2012
10万病原微生物基因组计划	美国加州大学、安捷伦科技公司、美国食品药品管理局、美国疾病预防控制中心、美国国立卫生研究院、北京师范大学、中国科学院微生物研究所、北京诺赛基因组研究中心	2014
第五届癌症系统生物学国际研讨会	来自中国和美国的癌症生物学、癌症临床、癌症组学数据分析的专家学者	2015

组学	工具和方法
基因组学	next generation sequencing
表观基因组学	ChIP-seq；
	Histon ChIP-seq；
	bisulfide sequencing
转录组学	RNA-seq；
	RNA-PET；
	CAGE
蛋白质组学	mass spectrometry；
	MALDI-imaging；
	CyTOF
代谢物组学	mass spectrometry；
	NMR；
	liquid & gas；
	chromatography

算法	特征和策略
MetaGene,MetaGeneAnnotator^[47]	双密码子的回归模型，基因长度等多种特征打分的动态规划模型
Orphelia^[48]	双密码子，TIS信号等多种特征的人工神经网络
MetaGeneMark^[49]	寡核苷酸回归模型，基因长度等多种特征的动态规划模型
FragGeneScan^[50]	基于密码子的隐马尔科夫模型
Glimmer-MG^[51]	基于Phymn分类后在各类上实施Glimmer预测方法
MetaProdigal^[52]	基于六连码回归模型和TIS信号的动态规划模型
AbundanceBin^[35]	基于k字词的方法，将序列的k字词向量进行比较，将相近的划归为一组
MetaCluster^[53]	基于k字词的方法，对序列物种进行划分
MetaGUN^[54]	序列按基因预测模型和翻译起始信号打分参数的选择分类

Bioinformatics methods for high-throughput DNA sequencing data

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