An effective approach for analyzing "prefinished" genomic sequence data

被引:0
作者
Kuehl, PM
Weisemann, JM
Touchman, JW
Green, ED
Boguski, MS [1 ]
机构
[1] Natl Lib Med, Natl Ctr Biotechnol Informat, NIH, Bethesda, MD 20894 USA
[2] NIH, Natl Human Genome Res Inst, Genome Technol Branch, Bethesda, MD 20892 USA
[3] Univ Maryland, Dept Mol & Cell Biol, Baltimore, MD 21201 USA
关键词
D O I
暂无
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Ongoing efforts to sequence the human genome are already generating large amounts of data, with substantial increases anticipated over the next few years. In most cases, a shotgun sequencing strategy is being used, which rapidly yields most of the primary sequence in incompletely assembled sequence contigs ("prefinished" sequence) and more slowly produces the final, completely assembled sequence ("finished" sequence). Thus, in general, prefinished sequence is produced in excess of finished sequence, and this trend is certain to continue and even accelerate over the next few years. Even at a prefinished stage, genomic sequence represents a rich source of important biological information that is of great interest to many investigators. However, analyzing such data is a challenging and daunting task, both because of its sheer volume and because it can change on a day-by-day basis. To facilitate the discovery and characterization of genes and other important elements within prefinished sequence, we have developed an analytical strategy and system that uses readily available software tools in new combinations. Implementation of this strategy for the analysis of prefinished sequence data from human chromosome 7 has demonstrated that this is a convenient, inexpensive, and extensible solution to the problem of analyzing the large amounts of preliminary data being produced by large-scale sequencing efforts. Our approach is accessible to any investigator who wishes to assimilate additional information about particular sequence data en route to developing richer annotations of a finished sequence.
引用
收藏
页码:189 / 194
页数:6
相关论文
共 50 条
[41]   A Cost Effective Approach for Analyzing Software Product Lines [J].
Narwane, Ganesh Khandu ;
Krishna, Shankara Narayanan ;
Bhattacharjee, Anup Kumar .
DISTRIBUTED COMPUTING AND INTERNET TECHNOLOGY, ICDCIT 2014, 2014, 8337 :212-223
[42]   Approximate approach to analyzing effective velocity of surface waves [J].
Chai Hua-you ;
Wei Chang-fu ;
Bai Shi-wei .
ROCK AND SOIL MECHANICS, 2008, 29 (01) :87-93
[43]   Approximate approach to analyzing effective velocity of surface waves [J].
Chai, Hua-You ;
Wei, Chang-Fu ;
Bai, Shi-Wei .
Yantu Lixue/Rock and Soil Mechanics, 2008, 29 (01) :87-93
[44]   From IMU Measurement Sequence to Velocity Estimate Sequence: An Effective and Efficient Data-Driven Inertial Odometry Approach [J].
Wang, Yingying ;
Cheng, Hu ;
Zhang, Ang ;
Meng, Max Q. -H. .
IEEE SENSORS JOURNAL, 2023, 23 (15) :17117-17126
[45]   A Hybrid Technique for the Periodicity Characterization of Genomic Sequence Data [J].
Epps, Julien .
EURASIP JOURNAL ON BIOINFORMATICS AND SYSTEMS BIOLOGY, 2009, (01)
[46]   Secure Sequence Similarity Search on Encrypted Genomic Data [J].
Mahdi, Md Safiur Rahman ;
Hasan, Mohammad Zahidul ;
Mohammed, Noman .
2017 IEEE/ACM SECOND INTERNATIONAL CONFERENCE ON CONNECTED HEALTH - APPLICATIONS, SYSTEMS AND ENGINEERING TECHNOLOGIES (CHASE), 2017, :205-213
[47]   Inferring the Direction of Introgression Using Genomic Sequence Data [J].
Thawornwattana, Yuttapong ;
Huang, Jun ;
Flouri, Tomas ;
Mallet, James ;
Yang, Ziheng .
MOLECULAR BIOLOGY AND EVOLUTION, 2023, 40 (08)
[48]   Novel selenoproteins identified from genomic sequence data [J].
Lescure, A ;
Gautheret, D ;
Krol, A .
PROTEIN SENSORS AND REACTIVE OXYGEN SPECIES, PT A, SELENOPROTEINS AND THIOREDOXIN, 2002, 347 :57-70
[49]   Secure Similar Sequence Query on Outsourced Genomic Data [J].
Cheng, Ke ;
Hou, Yantian ;
Wang, Liangmin .
PROCEEDINGS OF THE 2018 ACM ASIA CONFERENCE ON COMPUTER AND COMMUNICATIONS SECURITY (ASIACCS'18), 2018, :237-251
[50]   RIG: Recalibration and Interrelation of Genomic Sequence Data with the GATK [J].
McCormick, Ryan F. ;
Truong, Sandra K. ;
Mullet, John E. .
G3-GENES GENOMES GENETICS, 2015, 5 (04) :655-665