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The results were adjusted for gene length bias in DEGs (Young et al. 2010).
Gene Ontology (GO) enrichment analysis of differentially expressed genes was implemented by the GOseq R package, in which gene length bias was corrected.
The goseq bioconductor package (Robinson and Oshlack 2010) was used to account for the RNA length bias that is typical of RNA-Seq approaches (Oshlack and Wakefield 2009).
Examination of the counts of DE genes for each quartile of gene length also did not show any gene length bias (Fig S3).
We found little evidence of gene length bias using the edgeR package, though a relatively large effect was found using a Poisson model.
However, in this scenario shorter exons would be overrepresented due to the PCR amplicon length bias (typically a few hundred bp), making the mean and median underestimated.
The GRO data were normalized subtracting to each value the difference between the GRO and RPCC lowess smoothers in order to correct any probe length bias.
Furthermore, the development of new algorithms for estimation of gene expression from RNA-seq data is necessary to minimize length bias.
This is length bias.
Length bias will also be discussed.
But it does not remove length bias.
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