Research article
Comparative study of gene set enrichment methods
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* Corresponding author: Nicola Ancona ancona@ba.issia.cnr.it
1 Istituto di Studi sui Sistemi Intelligenti per l'Automazione, CNR, Via Amendola 122/D-I, Bari, Italy
2 Institute for Genome Science and Policy, Duke University, Durham, NC, USA
BMC Bioinformatics 2009, 10:275 doi:10.1186/1471-2105-10-275
Published: 2 September 2009Additional files
Additional file 1:
Supplement of simulations. Comparison of the methods in different simulation scenarios.
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Additional file 2:
Complete results in P53 data set. Complete results obtained in P53 data set.
Format: XLS Size: 524KB Download file
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Additional file 3:
Complete results in hypoxia data set. Complete results obtained in Hypoxia data set.
Format: XLS Size: 527KB Download file
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Additional file 4:
Complete results in bcat data set. Complete results obtained in α-catenin data set.
Format: XLS Size: 526KB Download file
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Additional file 5:
Complete results in e2f3 data set. Complete results obtained in E2F3 data set.
Format: XLS Size: 519KB Download file
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Additional file 6:
Complete results in myc data set. Complete results obtained in Myc data set.
Format: XLS Size: 512KB Download file
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Additional file 7:
Complete results in ras data set. Complete results obtained in Ras data set.
Format: XLS Size: 505KB Download file
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Additional file 8:
Complete results in src data set. Complete results obtained in Src data set.
Format: XLS Size: 500KB Download file
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Additional file 9:
Significant gene sets in P53 data set. Significant gene sets highlighted by RS and GLAPA in P53 data set.
Format: XLS Size: 19KB Download file
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Additional file 10:
Significant gene sets in breast data set. Significant gene sets highlighted by RS and GLAPA in breast cancer data set.
Format: XLS Size: 19KB Download file
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Additional file 11:
Significant gene sets in lung data set. Significant gene sets highlighted by RS and GLAPA in lung cancer data set.
Format: XLS Size: 21KB Download file
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