I am running the data preprocessing pipeline for scRNA-seq data presented here.
18.104.22.168 Gene expression
In addition to removing cells with poor quality, it is usually a good idea to exclude genes where we suspect that technical artefacts may have skewed the results. Moreover, inspection of the gene expression profiles may provide insights about how the experimental procedures could be improved.
It is often instructive to consider the number of reads consumed by the top 50 expressed genes.
By analyzing my data I have the following most expressed 50 genes (evaluating the total number of transcripts across cells):
Since I'll be working on log-transformed data, I assumed that the distributions of the top 50 genes were not excessively skewed. However, as you can see in the first plot, there are some samples (cells) with very high number of transcripts for the top gene. Is it something I should worry about? What other insights can I get from these two figures?
Original analysis (figure attached) was:
The distributions are relatively flat indicating (but not guaranteeing!) good coverage of the full transcriptome of these cells. However, there are several spike-ins in the top 15 genes which suggests a greater dilution of the spike-ins may be preferrable if the experiment is to be repeated.