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Mining for coexpression across hundreds of datasets using novel rank aggregation and visualization methods

Priit Adler1, Raivo Kolde23, Meelis Kull23, Aleksandr Tkachenko23, Hedi Peterson13, Jüri Reimand2 and Jaak Vilo23*

  • * Corresponding author: Jaak Vilo vilo@ut.ee

  • † Equal contributors

Author Affiliations

1 Institute of Molecular and Cell Biology, Riia 23, 51010 Tartu, Estonia

2 Institute of Computer Science, University of Tartu, Liivi 2-314, 50409 Tartu, Estonia

3 Quretec, Ülikooli 6a, 51003 Tartu, Estonia

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Genome Biology 2009, 10:R139  doi:10.1186/gb-2009-10-12-r139

Published: 4 December 2009

Additional files

Additional file 1:

The datasets were all on mouse platform Affymetrix U74Av2. In addition the analysis included an unpublished dataset that cannot be found in databases.

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Additional file 2:

A table listing datasets used for MCM complex study.

Format: XLS Size: 35KB Download file

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Additional file 3:

A table listing the 116 genes that occur in more than two of the six cohorts of subunits MCM1-MCM6, where each cohort contains 100 probesets with most correlation relative to the corresponding subunit.

Format: XLS Size: 17KB Download file

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Additional file 4:

The figure shows correlation between number of significant query results and the number of datasets where the query gene standard deviation exceeds certain threshold. The maximal correlation is achieved when the threshold is 0.29.

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