This study provides an assessment of the Fluidigm C1 platform for RNA sequencing of single mouse pancreatic islet cells. The system combines microfluidic technology and nanoliter-scale reactions. We sequenced 622 cells, allowing identification of 341 islet cells with high-quality gene expression profiles. The cells clustered into populations of α-cells (5%), β-cells (92%), δ-cells (1%), and pancreatic polypeptide cells (2%). We identified cell-type-specific transcription factors and pathways primarily involved in nutrient sensing and oxidation and cell signaling. Unexpectedly, 281 cells had to be removed from the analysis due to low viability, low sequencing quality, or contamination resulting in the detection of more than one islet hormone. Collectively, we provide a resource for identification of high-quality gene expression datasets to help expand insights into genes and pathways characterizing islet cell types. We reveal limitations in the C1 Fluidigm cell capture process resulting in contaminated cells with altered gene expression patterns. This calls for caution when interpreting single-cell transcriptomics data using the C1 Fluidigm system.