not necessarily a priority issue. but i think we can do this better..
heres an ex:
im assuming the counts differ for the two assays bc some of the samples failed qa while the workflow was running or something?? is there a way we can make this clearer? and maybe make clearer which samples failed?
or if there is another reason for the difference in counts, like in this ex:
how do we make clear the cause of the differences in counts?
We could simply collapse the diagram for mbio. If we want to highlight types of data each study has, a potentially low-cost option is to add labels after the study name (this info should also be in cards btw).
not necessarily a priority issue. but i think we can do this better..
heres an ex:
im assuming the counts differ for the two assays bc some of the samples failed qa while the workflow was running or something?? is there a way we can make this clearer? and maybe make clearer which samples failed?
or if there is another reason for the difference in counts, like in this ex:
how do we make clear the cause of the differences in counts?