RNA-Sequencing (RNA-Seq) has become a routine technology for investigating gene expression differences in comparative transcriptomic studies. Differential expression (DE) analysis of the isoforms of genes is just emerging now that expression (read counts) can be estimated with higher accuracy at the isoform level. Estimating the statistical power that can be achieved with a specific number of repeats is a key step in RNA-Seq analysis. The R library proper was developed to provide realistic empirical power analysis. However, proper uses differential expression methods more suited for power calculation of gene-level expression data. We propose extensions to this tool that would allow for power analysis which takes into account the specificities of isoforms expression. This was achieved by enabling the use of EBSeq, a DE approach well-tailored for isoform-level expression, as an additional analysis method within PROPER. The new extensions and exemplar code for their usage are freely available online at: https://github.com/agaye/proper_extension.
This research output has an Altmetric Attention Score of 10. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 13 February 2017.
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Outputs of similar age from Frontiers in Genetics
#8
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