wrapper functions

[patrickjdanaher]

I think it would help this get used if we had a wrapper function that made it simple to run. The main goals I have in mind are:

• Run resegmentation separately in each FOV to speed things up (running too many FOVs at once made R slow to a crawl)
• Make it easy to run the complete algorithm without a lot of preliminaries.

Here's one way to get there:

• [ ] Function for compiling all the necessary data from a single FOV (input: slide ID and FOV ID)
• [ ] Function for running the whole resegmentation procedure from the above data
• [ ] Function to gather data and run segmentation for all the slides/FOVs in a study.

[lidanwu]

Thanks for the suggestions. I have a few question regarding implementing the proposed wrapper functions.

• Are we assuming to have external reference profiles or existing cell typing outcomes for the data? If yes, the necessary data from each FOV is just the transcript data.frame, a file path to the file is all we need. If not, we need to read in the entire data at cell level to do cell clustering first.
• Wrapper around the whole re-segmentation procedure would contain the information for entire part II vignette. If we are happy with the choice of all tuning parameters, it's easy to wrap them up. If not, one might need to save the intermediate files and re-run the affected steps if the tuning parameters changed. Is that what we want for each FOV?
• If we run the procedure at FOV level, the post-run operation is simply to do rbind to gather all FOV's re-segment outputs into 1 data.frame. I haven't developed much visualization methods for the re-segmentation outcomes.

[lidanwu]

@patrickjdanaher Here is the wrapper to fastReseg_externalRef function to do the whole re-segmentation procedure with a transcript level data.frame, defined reference profiles and baseline cutoff for tLLR score and transcript number in resegmentation. I have also uploaded smaller example dataset such that one could run the function with the provided dataset and code list in function examples. Notice that the reference profiles and baseline cutoff are provided as input for current wrapper function but it would be better to extract them from the whole multi-slide multi-FOV experiment. I would next work on a function to enable the extraction of reference profiles and baseline cutoff from user input of either average per cell count of cell type x gene matrix or the true single cell count of cell ID x gene matrix.