Digital deconvolution approaches enhance the interrogation of expression profiles to identify the cellular population structure of individual samples, alleviating the requirement of additional neurostereology procedures. These approaches have been developed, tested, and applied to ascertain cellular composition altered in many traits [26–29]. However, digital deconvolution has not been applied to identify the cellular population structure from RNA-seq from human brain of AD cases and controls. Technical constraints restrict the dissociation of cells from the brains for very specific conditions [30–32]. Nevertheless, a limited number of RNA-seq from isolated cell populations from the brain have been generated [30–32]. Using these resources, we are now able to generate a reference panel for digital deconvolution of human brain bulk RNA-seq data.
