Over the past few years, the analysis of alternative splicing has emerged as an important new field in bioinformatics, and several recent large-scale studies have shown that alternative splicing can be analyzed in a high-throughput manner using DNA-microarray methods [46, 47] . Most of these studies used arrays particularly manufactured for analyzing alternative splicing, such as genomic tiling array and exon-exon junction array. Constructed without any priori knowledge of the possible exon content of a genomic sequence, the genomic tiling array [48, 49] is in principle capable of detecting novel alternative splicing events of diverse types, but it is in doubt whether their data will be readily interpretable as successful experiences remain insufficient [46] . On the other hand, although designed particularly to address the alternative splicing issue, exon and exon-exon junction arrays [49] were reported to be plagued by problematic probe specificity and unsatisfying hybridization efficiency because of the necessity of probe coverage across the full length of the gene (including 5' end) [5] . Many questions about the reproducibility of the amplification protocol, the quantitative accuracy, and the data analysis need to be addressed as a prerequisite to reliable quantitative analysis using these splicing arrays [50] . Given the current imperfection of splicing array techniques and inconvenience in deci-phering their generated data, it is an economic way to do large-scale investigations of alternative transcribing events with standard gene expression arrays, provided that the recognizing targets of the probes can be rigorously defined at the transcript level. Hu et al. proposed a primitive analysis method to explore alternative splicing with Affymetrix 3' gene expression arrays, though they regretted that only alternative splicing biased toward the 3'end of the gene can be detected in their way [51] . In the present paper, we conducted a large-scale alignment of the probe sequences in traditional gene expression arrays against the currently most comprehensive collection of transcript sequences, highlighting the probesets mapping to unique alternative transcripts unambiguously. For each of the two Affymetrix expression arrays tested in this study, we found over 40% of all probesets could be mapped to transcripts in a oneto-one manner, so our work strongly validate that it is feasible to analyze alternative splicing using traditional gene expression arrays. While the foregoing work contributed by Hu et al. remains as a qualitative analysis method aiming at detecting novel alternative splicing events, our work gives explicitly the relationship between the probesets and the currently known alternative transcript variants, which can be immediately exploited to facilitate quantitative analysis of alternative variants. As our mapping relationships are defined for the standard probesets of the traditional gene expression arrays, they can be conveniently exploited as the standard NetAffx annotation information, without any ad hoc influence on the widely applied experiment protocols or the routine data processing algorithms. In the demonstrative implementations of the novel annotation tables, we actually observed several examples of negatively correlated alternative variants (see Figure 2B for one of them), which will shed light on further studies of expression regulation of alternative transcript variants.