Advancements in Spatial Omics: Quality Control and Analytical Pipelines at ASOC

Good morning, everyone!

The ASOC proudly offers advanced spatial omics services through four cutting-edge platforms: Visium (HD)/Xenium In Situ from 10X Genomics and GeoMx DSP/CosMx SMI from Nanostring. Given the novelty of these platforms within the scientific community, there exists a lack of consensus regarding optimal quality control and data analysis workflows. Therefore, the Bioinformatics team at ASOC has been rigorously dedicated to developing comprehensive genomic pipelines, establishing robust quality control workflows, and implementing sophisticated algorithms designed to extract meaningful insights from biological data, linking these findings to relevant clinical contexts.

The Bioinformatics team initially prioritized the establishment of the GeoMx workflow, subsequently conducting a workshop on analyzing GeoMx data. Following this, they developed analytical pipelines tailored to Xenium and CosMx data in response to the increasing demand for investigations at the single-cell and subcellular levels. Customers seeking analyses using the Visium platform previously encountered delays due to the absence of a corresponding pipeline; however, we are pleased to announce that the Bioinformatics team has completed the development of analytical pipelines for all platforms.

While it is acknowledged that analysis pipelines may vary significantly from project to project, the quality control workflows remain critical to our operations. We conduct thorough sanity checks on our customers' data to provide insights into data quality and assess whether it meets the anticipated standards. We have diligently collected quality control metrics from each run, observing a progressive enhancement in data quality over time. These metrics enable us to determine the application of stringent or non-stringent filters and normalization techniques to ensure the delivery of high-quality data to our customers.

Selecting a region of interest (ROI) is crucial for a successful study and requires careful planning. When a user chooses a large ROI, it's common to observe many negative control probes in the panel that do not target mRNA (background). Consequently, more genes may be disregarded when the background signal is elevated. Conversely, if the ROI is too small, the collection might yield a limited number of nuclei, resulting in fewer quantifications. Throughout our projects, we have learned how to select ROIs strategically and can guide users in obtaining the highest quality data from GeoMx runs. The violin plots below illustrate the percentage of samples and genes included in the downstream analyses between the first batch (before 2024 Summer) and the second batch (after) conducted at the center. The second batch resulted in a significantly higher number of genes, providing customers more opportunities to explore a broader array of genes. We presented the data as percentages due to the difference in the total number of genes represented in the human and mouse panels.

The ASOC teams invest considerable effort in delivering quality data to our clients, and we are equipped to elucidate the factors influencing your analytical outcomes. It is essential to dissect these numbers and gain a comprehensive understanding of our current position within the field.

Lastly, we developed a decision tree below for selecting the spatial platform for your study. This diagram is intended as a general guide to help you orient platform selection based on key technical factors. However, the optimal spatial transcriptomics platform may vary depending on your specific study design, sample type and availability, research goals, and data analysis expectations. Always consult with us to ensure the chosen method aligns with your project's unique needs.

Thank you very much for your ongoing trust and collaboration. We look forward to using these exciting new capabilities to support your research!

Spatially yours,

The ASOC team