Method
SPACE: an algorithm to predict and quantify alternatively spliced isoforms using microarrays
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* Corresponding author: Angel Rubio arubio@ceit.es
1 CEIT and TECNUN, University of Navarra, San Sebastián, Spain
2 Integromics SL, Madrid, Spain
3 Computer Architecture Department, Facultad de Ciencias Físicas, Universidad Complutense de Madrid, Madrid 28040, Spain
4 Center for Applied Medical Research, University of Navarra, Pamplona, Spain
5 Department of Biochemistry, University of Navarra, Pamplona, Spain
6 Department of Histology and Pathology, University of Navarra, Pamplona, Spain
Genome Biology 2008, 9:R46 doi:10.1186/gb-2008-9-2-r46
Published: 29 February 2008Additional 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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