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Improving RNA-Seq expression estimates by correcting for fragment bias

Adam Roberts1, Cole Trapnell23, Julie Donaghey2, John L Rinn23 and Lior Pachter14*

Author Affiliations

1 Department of Computer Science, 387 Soda Hall, UC Berkeley, Berkeley, CA 94720, USA

2 Broad Institute, 7 Cambridge Center, Cambridge, MA 02142, USA

3 Department of Stem Cell and Regenerative Biology, 7 Divinity Avenue, Harvard University, Cambridge, MA 02138, USA

4 Departments of Mathematics and Molecular & Cell Biology, 970 Evans Hall, UC Berkeley, Berkeley, CA 94720, USA

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Genome Biology 2011, 12:R22  doi:10.1186/gb-2011-12-3-r22

Published: 16 March 2011

Abstract

The biochemistry of RNA-Seq library preparation results in cDNA fragments that are not uniformly distributed within the transcripts they represent. This non-uniformity must be accounted for when estimating expression levels, and we show how to perform the needed corrections using a likelihood based approach. We find improvements in expression estimates as measured by correlation with independently performed qRT-PCR and show that correction of bias leads to improved replicability of results across libraries and sequencing technologies.