mRNA expression profiles show differential regulatory effects of microRNAs between estrogen receptor-positive and estrogen receptor-negative breast cancer
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* Corresponding author: Mark Gerstein mark.gerstein@yale.edu
- Equal contributors
1 Program in Computational Biology and Bioinformatics, Yale University, George Street, New Haven, CT 06511, USA
2 State Key Laboratory of Genetic Engineering, Institute of Genetics, School of Life Science, Fudan University, Handan Road, Yangpu District, Shanghai, 200433, PR China
3 Department of Molecular Biophysics and Biochemistry, Yale University, Whitney Avenue, New Haven, CT 06520, USA
4 Department of Computer Science, Yale University, Prospect Street, New Haven, CT 06511, USA
Genome Biology 2009, 10:R90 doi:10.1186/gb-2009-10-9-r90
Published: 1 September 2009Additional files
Additional data file 1:
Distribution of miRNA target numbers for four prediction tools, PITA, miRanda, PicTar, and TargetScan. In addition, three different parameters in TargetScan were chosen and are denoted as 'Conserved', 'ContextScore ≥ -0.20' and 'All', respectively. On average, 6,949, 2,026, 1,563, 765, 426, and 210 targets per miRNA were predicted by PITA, TargetScan(All), miRanda, TargetScan(ContextScore ≥ -0.20), PicTar, and TargetScan(Conserved), respectively.
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Additional data file 2:
Includes seven sheets containing the complete results based on RE-scores from rank comparison and seven miRNA target predictions from PITA, miRanda, PicTar, the intersection of PITA and miRanda, TargetScan(Conserved), TargetScan(ContextScore ≥ -0.20), and TargetScan(All), respectively. The t-score, P-value, and adjusted P-value (FDR) of all miRNAs in the five breast cancer datasets are provided.
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Additional data file 3:
Additional data file 3 includes two sheets containing the complete results based on RE-scores calculated from expression comparison. In the two sheets, miRNA target predictions determined by the miRanda and PITA tools are used, respectively.
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Additional data file 4:
Expression levels of several miRNA processing genes in ER+ and ER- samples.
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