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Inference of Isoforms from Short Sequence Reads (Extended Abstract) Jianxing Feng1, Wei Li2, and Tao Jiang3 1 Comp. Sci. Dept., Tsinghua Univ., Beijing, China fengjx06@mails.tsinghua.edu.cn 2 Comp. Sci. Dept., Univ. of California, Riverside, CA liw@cs.ucr.edu 3 Comp. Sci. Dept., Univ. of California, Riverside, CA, and Tsinghua Univ., Beijing jiang@cs.ucr.edu Abstract. Due to alternative splicing events in eukaryotic species, the identification of mRNA isoforms (or splicing variants) is a difficult prob- lem. Traditional experimental methods for this purpose are time con- suming and cost ineffective. The emerging RNA-Seq technology provides a possible effective method to address this problem. Although the ad- vantages of RNA-Seq over traditional methods in transcriptome analysis have been confirmed by many studies, the inference of isoforms from mil- lions of short sequence reads (e.g., Illumina/Solexa reads) has remained computationally challenging. In this work, we propose a method to calcu- late the expression levels of isoforms and infer isoforms from short RNA- Seq reads using exon-intron boundary, transcription start site (TSS) and poly-A site (PAS) information. We first formulate the relationship among exons, isoforms, and single-end reads as a convex quadratic program, and then use an efficient algorithm (called IsoInfer) to search for isoforms. IsoInfer can calculate the expression levels of isoforms accurately if all the isoforms are known and infer novel isoforms from scratch. Our exper- imental tests on known mouse isoforms with both simulated expression levels and reads demonstrate that IsoInfer is able to calculate the expres- sion levels of isoforms with an accuracy comparable to the state-of-the-art statistical method and a 60 times faster speed. Moreover, our tests on both simulated and real reads show that it achieves a good precision and sensitivity in inferring isoforms when given accurate exon-intron bound- ary, TSS and PAS information, especiall