Method

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 Pio^4,5 , Luis M Montuenga^4,6 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

Abstract

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.