The performance of Single Cell RNA-Sequencing (scRNA-seq) protocols has yet to be evaluated. In this paper, we analyze the performance of scRNA-seq protocols in detecting gene abundance by investigating their dropout, that is the event of inability to detect gene abundance. In our research, we use 33 datasets that contain 689 million gene abundance reads obtained using the most commonly used protocols for scRNA-seq: Tang, SMARTer, and Smart-Seq. Our findings show that there is an increase in dropout rate detected in all datasets when going further in scanning the genes of the samples. Some datasets showed sharp increase in dropout while some showed a slight increase. Notably, the rise in dropout rate starts after passing the first third of the gene groups in the sample.