Table 2.

Recommendations for the selection of NormQ for RNASeq normalization.

Recommendations
1	Select well established marker genes that have a known distribution. If no marker genes are known, use DESeq2median or DESeq2spike to select at least five DEGs from each derived cluster profile, so as to reduce the probability (<0.005) of selecting outlier marker genes.
2	Ensure that the marker gene count across all replicates and sample section/condition are adequate (example >100).
3	Assess the relative abundance of the marker genes within each sample section/condition using RT-qPCR.
4	Use NormQ to renormalize the data.
5	Use degCheckFactor to assess the effectiveness of the size factors used. If the distribution between different sample sections/conditions are not well separated, then DESeq2median or DESeq2spike may be more appropriate methods as there is no asymmetry of your data.
6	Compare the NormQ, DESeq2median or DESeq2spike normalized data to the RT-qPCR derived profile to determine which technique best fits the data.