Closed teunbrand closed 4 years ago
For the following:
Group by sample or by result type?
Below are conceptual options.
Option 1:
discovery <- structure(list(
sampleA = list(
result1, # e.g. observed over expected
result2 # e.g. background or signal
),
sampleB = list(
result1,
result2
)
), class = "assayX_discovery", "discovery", "list")
Option 2:
discovery <- structure(list(
result1 = array(
sampleA,
sampleB
),
result2 = array(
sampleA,
sampleB
)
), class = "assayX_discovery", "discovery", "list")
Option 1 is easy to merge the results of different samples, option 2 is easy for computation and visualisation. @robinweide do you have strong opinions?
I would go for option 2. This would also allow for easy substitution of results by the user afterwards (e.g. pushing the same expected matrices for multiple samples).
For the following:
- [ ] APA
- [ ] ATA
- [ ] PESCAn
- [ ] RCP
- [ ] Saddle
- [ ] inter/intra TAD contacts
- [ ] domainogram
All these functions now have associated discovery classes.
Codename: Discovery