MIDAW: a web tool for statistical analysis of microarray data

被引:44
|
作者
Romualdi, C [1 ]
Vitulo, N [1 ]
Favero, MD [1 ]
Lanfranchi, G [1 ]
机构
[1] Univ Padua, Dipartimento Biol, CRIBI Biotechnol Ctr, I-35121 Padua, Italy
关键词
D O I
10.1093/nar/gki497
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
MIDAW (microarray data analysis web tool) is a web interface integrating a series of statistical algorithms that can be used for processing and interpretation of microarray data. MIDAW consists of two main sections: data normalization and data analysis. In the normalization phase the simultaneous processing of several experiments with background correction, global and local mean and variance normalization are carried out. The data analysis section allows graphical display of expression data for descriptive purposes, estimation of missing values, reduction of data dimension, discriminant analysis and identification of marker genes. The statistical results are organized in dynamic web pages and tables, where the transcript/ gene probes contained in a specific microarray platform can be linked ( according to user choice) to external databases (GenBank, Entrez Gene, UniGene). Tutorial files help the user throughout the statistical analysis to ensure that the forms are filled out correctly. MIDAW has been developed using Perl and PHP and it uses R/Bioconductor languages and routines. MIDAW is GPL licensed and freely accessible at http://muscle.cribi. unipd.it/midaw/.Perl and PHP source codes are available from the authors upon request.
引用
收藏
页码:W644 / W649
页数:6
相关论文
共 50 条
  • [41] A statistical framework for differential network analysis from microarray data
    Ryan Gill
    Somnath Datta
    Susmita Datta
    BMC Bioinformatics, 11
  • [42] An evaluation of statistical methods for DNA methylation microarray data analysis
    Li, Dongmei
    Xie, Zidian
    Le Pape, Marc
    Dye, Timothy
    BMC BIOINFORMATICS, 2015, 16
  • [43] Interactive Data Mining Tool for Microarray Data Analysis Using Formal Concept Analysis
    Tanabata, Takanari
    Hirose, Fumiaki
    Hashikami, Hidenobu
    Nobuhara, Hajime
    JOURNAL OF ADVANCED COMPUTATIONAL INTELLIGENCE AND INTELLIGENT INFORMATICS, 2012, 16 (02) : 273 - 281
  • [44] A Tool for Statistical Analysis on Network Big Data
    Ordonez, Carlos
    Johnson, Theodore
    Srivastava, Divesh
    Urbanek, Simon
    2017 28TH INTERNATIONAL WORKSHOP ON DATABASE AND EXPERT SYSTEMS APPLICATIONS (DEXA), 2017, : 32 - 36
  • [45] PROBER: Segmentation and Differential Analysis Tool for Tiling Microarray Data
    Ji, Guoli
    Wu, Xiaohui
    Xing, Denghui
    Li, Qingshun Quinn
    PROCEEDINGS OF THE 2009 2ND INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING AND INFORMATICS, VOLS 1-4, 2009, : 1517 - +
  • [46] MicrobiomeAnalyst: a web-based tool for comprehensive statistical, visual and meta-analysis of microbiome data
    Dhariwal, Achal
    Chong, Jasmine
    Habib, Salam
    King, Irah L.
    Agellon, Luis B.
    Xia, Jianguo
    NUCLEIC ACIDS RESEARCH, 2017, 45 (W1) : W180 - W188
  • [47] HT-RLS: High-Throughput web tool for analysis of DNA microarray data using RLS classifiers
    De Meo, P. D'Onorio
    Carrabino, D.
    D'Antonio, M.
    Sanna, N.
    Castrignano, T.
    Maglietta, R.
    D'Addabbo, A.
    Liuni, S.
    Mignone, F.
    Pesole, G.
    Ancona, N.
    CCGRID 2008: EIGHTH IEEE INTERNATIONAL SYMPOSIUM ON CLUSTER COMPUTING AND THE GRID, VOLS 1 AND 2, PROCEEDINGS, 2008, : 747 - +
  • [49] Statistical methods and microarray data - Reply
    Shi, Leming
    Jones, Wendell D.
    Jensen, Roderick V.
    Wolfinger, Russell D.
    Kawasaki, Ernest S.
    Herman, Damir
    Guo, Lei
    Goodsaid, Federico M.
    Tong, Weida
    NATURE BIOTECHNOLOGY, 2007, 25 (01) : 26 - 27
  • [50] Microarray data warehouse allowing for inclusion of experiment annotations in statistical analysis
    Fellenberg, K
    Hauser, NC
    Brors, B
    Hoheisel, JD
    Vingron, M
    BIOINFORMATICS, 2002, 18 (03) : 423 - 433