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

• Published in: Genome biology Vol. 9; no. 2; pp. R46 - 1908
• Main Authors: Anton, Miguel A, Gorostiaga, Dorleta, Guruceaga, Elizabeth, Segura, Victor, Carmona-Saez, Pedro, Pascual-Montano, Alberto, Pio, Ruben, Montuenga, Luis M, Rubio, Angel
• Format: Journal Article
• Language: English
• Published: London BioMed Central 29.02.2008
• Subjects: Algorithms; Alternative Splicing; Animal Genetics and Genomics; Animals; Bioinformatics; Biomedical and Life Sciences; Computational Biology - methods; Computer Simulation; Evolutionary Biology; Exons; Human Genetics; Humans; Life Sciences; messenger RNA; Method; microarray technology; Microbial Genetics and Genomics; Oligonucleotide Array Sequence Analysis; Plant Genetics and Genomics; Protein Isoforms - genetics; RNA precursors; Transcription, Genetic; Additional Data File; Reverse Transcription Polymerase Chain Reaction; Exon Cassette; Multiplicative Noise; Probe Expression
• ISSN: 1474-760X; 1465-6906; 1474-7596; 1474-760X; 1465-6914
• DOI: 10.1186/gb-2008-9-2-r46

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.