  Current popular methods in literature of RNA sequencing normalisation do not
account for gene length when compared across samples, whilst adjusting for
count biases in the data. This creates a gap in the normalisation as bigger
genes in RNA sequencing accumulate more reads due to shotgun sequencing
methods. As a result, the proportions of these reads inter-sample are not
properly accounted for in current normalisation methods. Alternatively, methods
which account for gene length do not account for the pan-sample biases in the
data by accounting for a central read average. Thus, in order to fill in the
gap in the literature, we propose a novel method of Transcripts Per Million
Ratio and its relatives in RNA-sequencing differential expression normalisation
that can be used in different conditions, which takes into account the gene
length as well as relative expression in normalisation.
