Supplementary Methods:

to

STAT6 and STAT1 are essential antagonistic regulators of cell survival in Hodgkin lymphoma

Daniela Baus1, Frank Nonnenmacher1,2, Sinje Jankowski1,2, Claudia Döring3, 5,

Christien Bräutigam2, Matthias Frank3, Martin-Leo Hansmann3 and Edith Pfitzner1, 2*

1Georg-Speyer-Haus, Institute for Biomedical Research, Paul-Ehrlich-Straße 42-44, 60596 Frankfurt,

2Friedrich-Schiller-University Jena, Department of Biochemistry and Biophysics, CMB -Center for Molecular Biomedicine, Hans-Knöll-Straße 2, D-07745 Jena
3Johann-Wolfgang-Goethe-University , Senckenberg Institute of Pathology, Theodor-Stern-Kai 7, D-60590 Frankfurt

5Johann-Wolfgang-Goethe-University, Institute for Informatics

Microarray data analysis

Data analysis yielding in some technical performance information (image inspection, number of detected genes, boxplots for and after normalization and calculation of the correlation coefficient between the replicates) was done using Expression Array System Software (Version 1.1.1, Applied Biosystems) and the Spotfire Decision Site Software (Spotfire®DecisionSite®8.1, AB1700Guides 081605). The quality of all microarrays is as recommended by Applied Biosystems. Probe intensity normalization for further analysis of gene expression was conducted using the percentile value (50%) of all genes. A list of differentially expressed genes was built by using the unpaired t-statistic (variance equal = TRUE). The correlation coefficient (Pearson Correlation) was above 0.96 in comparison of all genes of all replicates after percentile value normalization, which indicates a sufficient technical reproducibility. The complete analysis was done using the Spotfire Decision Site Software. The following genes are excluded in the final differentially expressed gene list:

Genes that are differentially expressed (p ≤ 0.05, FC (fold change) ≥ 2 or ≤ -2) between L1236 and L1236 scramble. Also genes that have a Flag value ≥ 5000 are excluded (Applied Biosystems 1700 Chemiluminescent Microarray Analyzer - User Guide).

Some additional genes were found when the data was reanalyzed with the statistical computing environment R (1). Additional software packages (ab1700, rma, multtest) were taken from the Bioconductor project (2). These data are not shown, but two of the genes identified in the reanalysis: UBE2D4 and NFAT5 were included in the validation experiments by quantitative RT-PCR shown in Fig. 2.

References:

1.  R Development Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria, 2005. URL http://www.R-project.org. ISBN 3-900051-07-0.

2.  Gentleman RC, Carey VJ, Bates DM, Bolstad, B Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, 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 JY, J Zhang J. Bioconductor: Open software development for computational biology and bioinformatics. Genome Biology 2004, 5(10): R80.