Correction of Technology-Related Artifacts in Serial Analysis of Gene Expression

Abstract

Serial analysis of gene expression (SAGE) is a powerful technique for measuring global gene expression through sampling of transcript tags. SAGE tag collections or libraries serve as a rich data source for differential gene expression analysis, transcriptome mapping, and gene discovery. Transcriptome mapping and gene discovery are facilitated by extensions of SAGE, e.g., Long SAGE, where the transcript tags are elongated by utilization of a different tagging enzyme. SAGE, as a sequencing-based technique, is prone to errors resulting in artifact SAGE tag sequences and erroneous tag numbers. A methodology to pinpoint and correct tag artifacts is necessary to fully exploit the value of large SAGE libraries. SAGEScreen is a tag sequence correction algorithm. The algorithm is a multistep procedure that addresses error rates and performs ditag and tag processing. The error rate estimates are based on a stochastic model of PCR and sequencing related mutations. The ditag processing step is essential for calculation of unbiased tag numbers, and the tag processing step allows for filtration of tag sequence artifacts and adjustment of tag numbers.