SPACE: an algorithm to predict and quantify alternatively spliced isoforms using microarrays

Miguel A Anton¹ , Dorleta Gorostiaga¹ , Elizabeth Guruceaga¹ , Victor Segura¹ , Pedro Carmona-Saez² , Alberto Pascual-Montano³ , Ruben Pio⁴^,5 , Luis M Montuenga⁴^,6 and Angel Rubio¹

¹CEIT and TECNUN, University of Navarra, San Sebastián, Spain

²Integromics SL, Madrid, Spain

³Computer Architecture Department, Facultad de Ciencias Físicas, Universidad Complutense de Madrid, Madrid 28040, Spain

⁴Center for Applied Medical Research, University of Navarra, Pamplona, Spain

⁵Department of Biochemistry, University of Navarra, Pamplona, Spain

⁶Department of Histology and Pathology, University of Navarra, Pamplona, Spain

author email corresponding author email

Genome Biology 2008, 9:R46doi:10.1186/gb-2008-9-2-r46


Published:	29 February 2008

Subject areas: Bioinformatics, Molecular biology, Genome studies

Additional files

Additional data file 1:

Figures S1-S8 show the structure of all genes and transcripts, as well as probe positions, that have been used to make the synthetic data in the simulations for the eight selected genes with SPACE algorithm. Figure S9 shows an example of the affinity, property and concentration matrices according to Wang et al.'s model. Figure S10 shows the results of applying SPACE algorithm to six arrays with two isoforms of CASP2 gene (synthetic data). Three of these simulated arrays had one concentration ratio and the other three the opposite ratio. Figures S11-S22 show the results obtained in the simulations done for 100 random genes selected from the human genome (synthetic data).

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Additional data file 2:

This zipped file includes the Matlab data files (.mat) for the three genes in Johnson et al.'s study and the code for the algorithms to predict number of transcripts, concentrations and structure. A convenient demo script file (demojohnson.m) is included to show how to use the functions.

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