There is no standard whether to use spike-in control or not, I guess it varies case to case. During sequencing there are so many unknown factors one can’t control, so including a spike-in would be better as this would allow to evaluate performance of library preparation and sequencing, and thus less unbiased call for differential gene expression in later stages. However, there have been studies that says the spike-in controlled data may be very biased to various degree unless the experiments are designed in a careful way to preserve and capture true biological variations represented in your sample. As the spike-in datasets represent only technical replicates with minimal variation, this could be complemented with more practical comparisons in real datasets with true biological replicates. For example, this study (http://europepmc.org/articles/pmc4404308
) reports that spike-ins are not reliable enough to be used in standard global-scaling or regression-based normalization procedures. One of the advantages of using spike controls for normalization is the possibility of relaxing the common assumption that majority of the genes are not DE between the conditions under study. So if you want to use the spike-ins for normalization, two conditions must be satisfied: (i) spike-in read counts are not affected by the biological factors of interest, and (ii) the unwanted variation should affect the spike-in and gene read counts similarly.
One should not confuse with the definition of spike-ins, the one between PhiX (used for quality-control during sequencing) and the spike-ins for normalization purposes. To some extent, both are useful for quality control and for library-size normalization. There is an External RNA Control Consortium (ERCC) that had developed a set of 92 synthetic spike-in standards that are commercially available and relatively easy to add to a typical library preparation. So you can select various formulation mixes of controls from these kits (or could be custom made) and use in your experiments. Ambion (Life Technologies) is the only company that manufactures such spike-in controls for normalization purpose. You can find step-by-step details here on how and when to use Spike-ins https://tools.thermofisher.com/content/sfs/manuals/cms_086340.pdf
. The main idea here is to achieve a standard measure for data comparison across gene expression experiments, measure sensitivity (lower the limit of detection) and dynamic range of an experiment, and quantitate differential gene expression.