Finally, it can be helpful to examine the expression distribution for genes of interest. The following plots will show the expression of selected genes.
❱❱❱ ACTION ❰❰❰
Use the following code block to define some genes of interest that you would like to inspect. Note that you should restrict this to a handful of particularly interesting genes, as large gene lists will generate a lot of data and a lot of plots, which can reduce the performance of these notebooks.
Define your gene lists using a named list, with the names being identicial to those used within the comparisons list defined above for running the differential expression analyses. For example:
genes_to_plot <- list(
b_cells = c("CD79A", "IGHD"),
t_cells = c("CD3D", "CD3E", "CD247")
)"Plot has no data; skipping plotting or handling accordingly."
Finally, it can be helpful to examine the expression distribution for genes of interest. The following plots will show the expression of selected genes.
❱❱❱ ACTION ❰❰❰
Use the following code block to define some genes of interest that you would like to inspect. Note that you should restrict this to a handful of particularly interesting genes, as large gene lists will generate a lot of data and a lot of plots, which can reduce the performance of these notebooks.
Define your gene lists using a named list, with the names being identicial to those used within the
comparisonslist defined above for running the differential expression analyses. For example:"Plot has no data; skipping plotting or handling accordingly."