BLASTGrabber: a bioinformatic tool for visualization, analysis and sequence selection of massive BLAST data

被引:6
|
作者
Neumann, Ralf Stefan [1 ,2 ]
Kumar, Surendra [1 ,2 ]
Haverkamp, Thomas Hendricus Augustus [3 ]
Shalchian-Tabrizi, Kamran [1 ,2 ]
机构
[1] Univ Oslo, Sect Genet & Evolutionary Biol EVOGENE, Oslo, Norway
[2] Univ Oslo, CEDE, Oslo, Norway
[3] Univ Oslo, Dept Biosci, Ctr Ecol & Evolutionary Synth, Oslo, Norway
来源
BMC BIOINFORMATICS | 2014年 / 15卷
关键词
Analysis; BLAST; High-throughput; Taxonomy; Text-mining; Visualization; DISCOVERY; TAXONOMY; OUTPUT;
D O I
10.1186/1471-2105-15-128
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Background: Advances in sequencing efficiency have vastly increased the sizes of biological sequence databases, including many thousands of genome-sequenced species. The BLAST algorithm remains the main search engine for retrieving sequence information, and must consequently handle data on an unprecedented scale. This has been possible due to high-performance computers and parallel processing. However, the raw BLAST output from contemporary searches involving thousands of queries becomes ill-suited for direct human processing. Few programs attempt to directly visualize and interpret BLAST output; those that do often provide a mere basic structuring of BLAST data. Results: Here we present a bioinformatics application named BLASTGrabber suitable for high-throughput sequencing analysis. BLASTGrabber, being implemented as a Java application, is OS-independent and includes a user friendly graphical user interface. Text or XML-formatted BLAST output files can be directly imported, displayed and categorized based on BLAST statistics. Query names and FASTA headers can be analysed by text-mining. In addition to visualizing sequence alignments, BLAST data can be ordered as an interactive taxonomy tree. All modes of analysis support selection, export and storage of data. A Java interface-based plugin structure facilitates the addition of customized third party functionality. Conclusion: The BLASTGrabber application introduces new ways of visualizing and analysing massive BLAST output data by integrating taxonomy identification, text mining capabilities and generic multi-dimensional rendering of BLAST hits. The program aims at a non-expert audience in terms of computer skills; the combination of new functionalities makes the program flexible and useful for a broad range of operations.
引用
收藏
页数:11
相关论文
共 50 条
  • [1] BLASTGrabber: a bioinformatic tool for visualization, analysis and sequence selection of massive BLAST data
    Ralf Stefan Neumann
    Surendra Kumar
    Thomas Hendricus Augustus Haverkamp
    Kamran Shalchian-Tabrizi
    BMC Bioinformatics, 15
  • [2] BLASTGrabber: A bioinformatic tool for visualization, analysis and sequence selection of massive BLAST data
    Shalchian-Tabrizi, Kamran (kamran@ibv.uio.no), 1600, BioMed Central Ltd, United Kingdom (15):
  • [3] BLASTGrabber: A bioinformatic tool for visualization, analysis and sequence selection of massive BLAST data
    Neumann, Ralf S.
    Kumar, Surendra
    Haverkamp, Thomas Hendricus A.
    Shalchian-Tabrizi, Kamran
    BMC Bioinformatics, 2014, 15 (01)
  • [4] BARD: A visualization tool for biological sequence analysis
    Spell, R
    Brady, R
    Dietrich, F
    INFOVIS 2002: IEEE SYMPOSIUM ON INFORMATION VISUALIZATION 2003, PROCEEDINGS, 2003, : 219 - 225
  • [5] MolSpace: a computer desktop tool for visualization of massive molecular data
    Takahashi, Y
    Konji, M
    Fujishima, S
    JOURNAL OF MOLECULAR GRAPHICS & MODELLING, 2003, 21 (05): : 333 - 339
  • [6] An Analysis and Visualization Tool for DBLP Data
    Burch, Michael
    Pompe, Daniel
    Weiskopf, Daniel
    2015 19TH INTERNATIONAL CONFERENCE ON INFORMATION VISUALISATION IV 2015, 2015, : 163 - 170
  • [7] Massive Railway Operating Data Visualization; a Tool for RATP Operating Expert
    Dimanche, Vincent
    Goupil, Alban
    Philippot, Alexandre
    Riera, Bernard
    Urban, Alain
    Gabriel, Gerard
    IFAC PAPERSONLINE, 2017, 50 (01): : 15841 - 15846
  • [8] Massive Data Visualization Analysis Analysis of current visualization techniques and main challenges for the future
    Perez Cota, Manuel
    Diaz Rodriguez, Maria
    Ramon Gonzalez-Castro, Miguel
    Moreira Goncalves, Ramiro Manuel
    2017 12TH IBERIAN CONFERENCE ON INFORMATION SYSTEMS AND TECHNOLOGIES (CISTI), 2017,
  • [9] Massive Data Visualization Analysis Analysis of current visualization techniques and main challenges for the future
    Perez Cota, Manuel
    Diaz Rodriguez, Maria
    Gonzalez Castro, Miguel Ramon
    Moreira Goncalves, Ramiro Manuel
    SISTEMAS E TECNOLOGIAS DE INFORMACAO, VOL I, 2011, : 37 - +
  • [10] A web-based bioinformatic tool LYNX for targeted LYmphoid NeXt-generation sequencing data analysis and visualization for hematooncology
    Reigl, Tomas
    Porc, Jakub
    Navrkalova, Veronika
    Hynst, Jakub
    Pal, Karol
    Stranska, Kamila
    Kotaskova, Jana
    Pospisilova, Sarka
    Plevova, Karla
    EUROPEAN JOURNAL OF HUMAN GENETICS, 2024, 32 : 680 - 680