Conventional methods for diagnosing and analyzing cancer cells are based on histology, genetic analysis, and protein analysis. Specific genotypes or proteins have been used as biomarkers in identifying cancer cells with specific phenotypes. Despite recent advances in cancer research, quantifying the heterogeneous tumor cell populations has been one of the main challenges in cancer diagnosis and prognosis [1]. The heterogeneous population of cells in the same tissues at different tumor development stages makes analyzing genetic alteration in tumors complicated. Methods conventionally used to study the heterogeneity of cancer cells are based on bulk analysis requiring large number of cells for assay. The resultant measurements are an average from multiple cells. As a result, any single protein or biomarker assay is not capable of determining the cellular heterogeneity of tumor [2]. To overcome such challenges, technologies capable of conducting reliable and high throughput sample analysis with single cell resolution is crucial.

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