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 2008Abstract
Exon and exon+junction microarrays are promising tools for studying alternative splicing. Current analytical tools applied to these arrays lack two relevant features: the ability to predict unknown spliced forms and the ability to quantify the concentration of known and unknown isoforms. SPACE is an algorithm that has been developed to (1) estimate the number of different transcripts expressed under several conditions, (2) predict the precursor mRNA splicing structure and (3) quantify the transcript concentrations including unknown forms. The results presented here show its robustness and accuracy for real and simulated data.