Quantitative comparison of EST libraries requires compensation for systematic biases in cDNA generation

Author:

Liu Donglin,Graber Joel H

Abstract

Abstract Background Publicly accessible EST libraries contain valuable information that can be utilized for studies of tissue-specific gene expression and processing of individual genes. This information is, however, confounded by multiple systematic effects arising from the procedures used to generate these libraries. Results We used alignment of ESTs against a reference set of transcripts to estimate the size distributions of the cDNA inserts and sampled mRNA transcripts in individual EST libraries and show how these measurements can be used to inform quantitative comparisons of libraries. While significant attention has been paid to the effects of normalization and substraction, we also find significant biases in transcript sampling introduced by the combined procedures of reverse transcription and selection of cDNA clones for sequencing. Using examples drawn from studies of mRNA 3'-processing (cleavage and polyadenylation), we demonstrate effects of the transcript sampling bias, and provide a method for identifying libraries that can be safely compared without bias. All data sets, supplemental data, and software are available at our supplemental web site [1]. Conclusion The biases we characterize in the transcript sampling of EST libraries represent a significant and heretofore under-appreciated source of false positive candidates for tissue-, cell type-, or developmental stage-specific activity or processing of genes. Uncorrected, quantitative comparison of dissimilar EST libraries will likely result in the identification of statistically significant, but biologically meaningless changes.

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Structural Biology

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