Sequential Fitting Strategies For Models of short RNA Sequencing Data

After a (really long!) hiatus I am reactivating my statistical blog. The first article  concerns the clarification of a point made in the manual of our recently published statistical model for short RNA sequencing data.The background for this post, in case one wants to skip reading the manuscript (please do read it !), centers around the limitations of existing methods for the analysis of data for this very promising class of biomarkers. To overcome these limitations our group comprised from investigators from Division of Nephrology, University of New Mexico and the Galas Lab at Pacific Northwest Research Institute introduced a novel method for the analysis of short RNA sequencing (sRNAseq) data. This method (RNAseqGAMLSS), which was derived from first principles modeling of the short RNAseq process, was shown to have a number of desirable properties in an analysis of nearly 200 public and internal…
Original Post: Sequential Fitting Strategies For Models of short RNA Sequencing Data