MADAM - An open source meta-analysis toolbox for R and Bioconductor

被引:18
作者
Kugler, Karl G. [1 ]
Mueller, Laurin A. J. [1 ]
Graber, Armin [1 ]
机构
[1] UMIT, Inst Bioinformat & Translat Res, Eduard Walln~fer Zentrum 1, A-6060 Tyrol, Austria
来源
SOURCE CODE FOR BIOLOGY AND MEDICINE | 2010年 / 5卷 / 01期
关键词
D O I
10.1186/1751-0473-5-3
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Background: Meta-analysis is a major theme in biomedical research. In the present paper we introduce a package for R and Bioconductor that provides useful tools for performing this type of work. One idea behind the development of MADAM was that many meta-analysis methods, which are available in R, are not able to use the capacities of parallel computing yet. In this first version, we implemented one meta-analysis method in such a parallel manner. Additionally, we provide tools for combining the results from a set of methods in an ensemble approach. Functionality for visualization of results is also provided. Results: The presented package enables the carrying out of meta-analysis either by providing functions directly or by wrapping them to existing implementations. Overall, five different meta-analysis methods are now usable through MADAM, along with another three methods for combining the corresponding results. Visualizing the results is eased by three included functions. For developing and testing meta-analysis methods, a mock up data generator is integrated. Conclusions: The use of MADAM enables a user to focus on one package, in turn enabling them to work with the same data types across a set of methods. By making use of the snow package, MADAM can be made compatible with an existing parallel computing infrastructure. MADAM is open source and freely available within CRAN http://cran.r-project.org.
引用
收藏
页数:5
相关论文
共 10 条
[1]   MAID : An effect size based model for microarray data integration across laboratories and platforms [J].
Borozan, Ivan ;
Chen, Limin ;
Paeper, Bryan ;
Heathcote, Jenny E. ;
Edwards, Aled M. ;
Katze, Michael ;
Zhang, Zhaolei ;
McGilvray, Ian D. .
BMC BIOINFORMATICS, 2008, 9 (1) :305
[2]   Combining multiple microarray studies and modeling interstudy variation [J].
Choi, Jung Kyoon ;
Yu, Ungsik ;
Kim, Sangsoo ;
Yoo, Ook Joon .
BIOINFORMATICS, 2003, 19 :i84-i90
[3]  
Fisher R.A., 1925, MATH PROC CAMBRIDGE, DOI 10.1111/j.2397-2335.1926.tb01837.x
[4]   Bioconductor: open software development for computational biology and bioinformatics [J].
Gentleman, RC ;
Carey, VJ ;
Bates, DM ;
Bolstad, B ;
Dettling, M ;
Dudoit, S ;
Ellis, B ;
Gautier, L ;
Ge, YC ;
Gentry, J ;
Hornik, K ;
Hothorn, T ;
Huber, W ;
Iacus, S ;
Irizarry, R ;
Leisch, F ;
Li, C ;
Maechler, M ;
Rossini, AJ ;
Sawitzki, G ;
Smith, C ;
Smyth, G ;
Tierney, L ;
Yang, JYH ;
Zhang, JH .
GENOME BIOLOGY, 2004, 5 (10)
[5]   A comparison of meta-analysis methods for detecting differentially expressed genes in microarray experiments [J].
Hong, Fangxin ;
Breitling, Rainer .
BIOINFORMATICS, 2008, 24 (03) :374-382
[6]   Comparison and meta-analysis of microarray data: from the bench to the computer desk [J].
Moreau, Y ;
Aerts, S ;
De Moor, B ;
De Strooper, B ;
Dabrowski, M .
TRENDS IN GENETICS, 2003, 19 (10) :570-577
[7]  
Rhodes DR, 2002, CANC RES
[8]   A direct approach to false discovery rates [J].
Storey, JD .
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 2002, 64 :479-498
[9]   Missing value estimation methods for DNA microarrays [J].
Troyanskaya, O ;
Cantor, M ;
Sherlock, G ;
Brown, P ;
Hastie, T ;
Tibshirani, R ;
Botstein, D ;
Altman, RB .
BIOINFORMATICS, 2001, 17 (06) :520-525
[10]   Significance analysis of microarrays applied to the ionizing radiation response [J].
Tusher, VG ;
Tibshirani, R ;
Chu, G .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2001, 98 (09) :5116-5121