Noise filtering and nonparametric analysis of microarray data underscores discriminating markers of oral, prostate, lung, ovarian and breast cancer

Virginie M Aris¹^,2^,3 , Michael J Cody¹ , Jeff Cheng¹^,2 , James J Dermody³ , Patricia Soteropoulos¹^,3 , Michael Recce¹^,2 and Peter P Tolias¹^,3^,4

¹Center for Applied Genomics, Public Health Research Institute, Newark, NJ 07103, USA

²Center for Computational Biology, New Jersey Institute of Technology, Newark, NJ 07103, USA

³Dept of Microbiology and Molecular Genetics, UMDNJ-New Jersey Medical School, Newark, NJ 07103, USA

⁴Current address: Ortho-Clinical Diagnostics a Johnson & Johnson Company, Raritan, NJ 08869, USA

author email corresponding author email

BMC Bioinformatics 2004, 5:185doi:10.1186/1471-2105-5-185


Published:	29 November 2004

Additional files

Additional File 2:

Assessing the noise level and trust threshold for differential expression on Affymetrix GeneChips. This document compares the noise from MAS5, RMA and dChip and presents the sensitivity analysis for the noise model parameters using the Latin square replicate data set.

Format: DOC Size: 410KB Download file

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Additional File 3:

Gene markers for prostate, breast, ovarian, oral, and lung cancer. This file presents the Top Er scores for each cancer studied when compared to its normal tissue. There is a result table with gene information for each cancer on separate tabs.

Format: XLS Size: 197KB Download file

This file can be viewed with: Microsoft Excel Viewer

Additional File 1:

Gene markers that distinguish between prostate, breast, ovarian, oral, and lung cancer. This file presents the Er scores of genes expression levels that are consistently up or down in a given cancer compared to its normal tissue (Er>0.9) but not in any of the other four cancers (Er<0.6).

Format: XLS Size: 44KB Download file

This file can be viewed with: Microsoft Excel Viewer