I need input on what is a sensible data representation.
I'm trying to make the legend accompanying the sparklines/scatterplots a bit "smarter", basically having sensible defaults (that you can override, don't worry):
(aside: I've used an interpolation tool to increase the solar9 gradient to a solar256 gradient, and also added the YlGnBu scale as a Heatmap2 option - being protanomalous the latter is easier to read for me)
The issue is that some metadata fields, like _LogCV or _tSNE1 & _tSNE2 tend to end up with (nearly) unique values for each column/row entry. This leads to these silly results:
(also, in the process of opening this issue I realised that gene data is no longer being sorted. Ignore that visual error for now, I'll fix that soon)
There's also the fact that zero values often representing missing data:
So I think that it would make sense to "bin" numerical data before creating a legend. Here are my thoughts so far:
determine min/max values to determine dynamic range
ignore zero values for this purpose, since it's often used to represent "missing" data
bin to N value ranges
determine if ranges needs to be log-scaled (I guess checking if the attribute name starts with _Log would work? And gene values?)
if zero-values are present they get their own bin
display value ranges in legend (allow filtering on these ranges? This would somewhat complicate the code/data structure, but if you consider this worth it I'll build it)
color bins by mapping to the gradient palette
Is this a valid, clear way of representing the data, or would you prefer something else? How many bins would you consider sensible? Do you need filtering capabilities for these bins?
I need input on what is a sensible data representation.
I'm trying to make the legend accompanying the sparklines/scatterplots a bit "smarter", basically having sensible defaults (that you can override, don't worry):
(aside: I've used an interpolation tool to increase the
solar9
gradient to asolar256
gradient, and also added the YlGnBu scale as aHeatmap2
option - being protanomalous the latter is easier to read for me)The issue is that some metadata fields, like
_LogCV
or_tSNE1
&_tSNE2
tend to end up with (nearly) unique values for each column/row entry. This leads to these silly results:(also, in the process of opening this issue I realised that gene data is no longer being sorted. Ignore that visual error for now, I'll fix that soon)
There's also the fact that zero values often representing missing data:
So I think that it would make sense to "bin" numerical data before creating a legend. Here are my thoughts so far:
N
value ranges_Log
would work? And gene values?)Is this a valid, clear way of representing the data, or would you prefer something else? How many bins would you consider sensible? Do you need filtering capabilities for these bins?
Thanks for your feedback,
/Job