* This project was supported in part by an NIH grant R01CA68822.

Description

WebArray is a web platform for analysis of microarray data. The computations are powered by R language and Bioconductor. Benefited from Bioconductor, WebArray is able to deal with intensity data files of many different types, like Affymetrix, Agilent, Genepix, QuantArray, etc. WebArray offers many conventional functions for microarray data analysis:

Background Substration Including several methods.
Normalization For within-array normalization, methods cover print-tip loess, global loess, median, robust spline; for between-array normalization, methods include Aquantile, Gquantile, PCA, Quantile, Rquantile, Scale and vsn.
Analysis limma-based linear model statistical analysis (including FDR calculation with SPLOSH).
Genome Mapping Available for different genome types.

To use this platform, users need to register to obtain a user ID for purposes of uploading data, submitting requests and collecting results. Please notice that a browser with JavaScript and cookie support is also required. A successful analysis will result in some text files and charts. After submitting a request for analysis, the user doesn't have to wait for results. He/she can browse results online or download results files later.

Citation

A paper in relation to WebArray was published on BMC Bioinformatics:

Xia X, McClelland M, Wang Y. WebArray: an online platform for microarray data analysis. BMC Bioinformatics. 2005, 6(1): 306.
[Abstract] [Full Text] [PDF]

The WebArray can be cited in Endnote format (download HERE), or in BibTex format:

@Article{WEBARRAY,
  author = {XiaoQin Xia, Michael McClelland and Yipeng Wang},
  title = {WebArray: an online platform for microarray data analysis},
  journal = {BMC Bioinformatics},
  volume = {6},
  year = {2005},
  pages = {306},
  url = {http://www.biomedcentral.com/1471-2105/6/306}
}

Download

WebArray is under GNU GPL, you may download the WebArray source codes following the links below.
WebArray-1.1: webarray-1.1.tar.gz and README (packed on 2007/10/05)

WebArray News

2006/10/19 R was upgraded to version 2.4.0. Accordingly Bioconductor was upgraded to version 1.9. Then more Affymetrix GeneChip types are supported.

2006/10/19 The interface between python and R language was switch from Rpy to pipe offered by python, this allows R run faster.

2006/02/03 Gal file is not necessary any longer for those data files with gene & grid information.

2006/02/03 Source codes are available for downloading.

Problems

Please report bugs to Xiao-Qin Xia ( x x i a @ s k c c . o r g )
For questions about analysis, please contact Yipeng Wang ( y w a n g @ s k c c . o r g )

Last Updated: 2007/02/08

2006/10/19	R was upgraded to version 2.4.0. Accordingly Bioconductor was upgraded to version 1.9. Then more Affymetrix GeneChip types are supported.
2006/10/19	The interface between python and R language was switch from Rpy to pipe offered by python, this allows R run faster.
2006/02/03	Gal file is not necessary any longer for those data files with gene & grid information.
2006/02/03	Source codes are available for downloading.