A single-cell multi-omics approach can provide a full resolution of cancer in its heterogeneous mixture of cells with varied states, allowing laboratories to reveal clonal heterogeneity and lead to more informed research on disease and therapeutic development.
Challenges still remain for those laboratories, with integrating and analyzing these multi-analyte data to gain truly meaningful biological insights.
In this webinar, we will provide an introduction to single-cell multi-omic data analysis, using the latest tools developed to enable co-analysis of SNVs, CNVs and protein expression. This also includes visualization tools that facilitate linking genetic variation to protein expression to obtain proteogenomic information required to identify drug resistance, understand treatment response, and predict relapse.
Topics will include: