Is there an optimal way to do single-cell RNA-seq counts normalization? Most RNA-seq normalization tools are designed with bulk samples in mind and assume a certain distribution of reads. With bulk RNA-seq, you have millions of reads per sample with relatively consistent coverage across samples. With single-cell experiments, you have much fewer total reads and many low expressing genes will be completely absent from many samples. I am curious how much I should worry about that and if there is a good way to account for that.