Traditional bulk RNA sequencing (RNA-Seq) is a powerful method for studying the transcriptome by identifying the full catalog of transcripts, defining gene structures, and accurately measuring gene expression levels. This can also be harnessed as a means for unbiased expression screening across large numbers of samples. However, this approach cannot detect differences that arise between individual cells in complex environments. Single-cell RNA-Seq, on the other hand, allows for deep analysis of the transcriptome at the single-cell level in diverse heterogenous cell populations, uncovering cellular differences that are masked by bulk RNA-Seq. Digital spatial profiling takes this to the next level by combining high-plex gene expression profiling with the spatial resolution of immunohistochemistry, enabling high-resolution transcriptomics within the complexity of intact tissue samples. Finally, protein biomarker discovery and quantification enables identification and measurement of disease signatures to bridge the gap between genomics, transcriptomics, and phenotypes, resulting in effective, targeted, and safer therapies for patients. ​

In part 2, we will take a deeper dive into the analyzed results to elaborate on what conclusions we can draw from each method, as well as how these different methodologies can complement and/or confirm findings