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.
Highlights
RNA-Seq technology offers the possibility of accurately measuring transcript abundances in a sample of RNA by sequencing of double stranded cDNA [1]
Estimating fragment bias in existing protocols Fragment counts in an RNA-Seq experiment are determined by two different phenomena: fragments originating from highly expressed transcripts will appear more often in the data than those originating from lowerexpressed transcripts, and library preparations include biases that may preferentially select some potential fragments over others
Bias correction improves expression estimates Our results confirm that bias correction improves expression estimates and should be used to correct bias introduced in library preparations and by sequencing technologies
Summary
RNA-Seq technology offers the possibility of accurately measuring transcript abundances in a sample of RNA by sequencing of double stranded cDNA [1]. Current technological limitations of sequencers require that the cDNA molecules represent only partial fragments of the RNA being probed. The cDNA fragments are obtained by a series of steps, often including reverse transcription primed by random hexamers (RH), or by oligo (dT). Most protocols include a fragmentation step, typically RNA hydrolysis or nebulization, or alternatively cDNA fragmentation by DNase I treatment or sonication. Many sequencing technologies require constrained cDNA lengths, so a final gel cutting step for size selection may be included.
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