Original report (archived issue) by Shaun Johnstone (Bitbucket: shjohnst, GitHub: shjohnst).
If lyse is left running for weeks at a time, and shots are not manually removed from it, the dataframe that is passed to multi-shot analysis scripts can become quite large, and take 10's of seconds to transfer.
Most multi-shot routines in our lab will immediately throw out the majority of that dataframe, taking either the last n sequences, all the shots from the current day, or some other subset.
It would make sense for multi-shot scripts to be able to ask for this subset of the dataframe in the first place, e.g. by asking for df=data(sequences=number_of_sequences_to_analyse) or df=data(date=today)
This should prevent multi-shot analysis from slowing down when lyse is not restarted often.
Original report (archived issue) by Shaun Johnstone (Bitbucket: shjohnst, GitHub: shjohnst).
If lyse is left running for weeks at a time, and shots are not manually removed from it, the dataframe that is passed to multi-shot analysis scripts can become quite large, and take 10's of seconds to transfer.
Most multi-shot routines in our lab will immediately throw out the majority of that dataframe, taking either the last n sequences, all the shots from the current day, or some other subset.
It would make sense for multi-shot scripts to be able to ask for this subset of the dataframe in the first place, e.g. by asking for df=data(sequences=number_of_sequences_to_analyse) or df=data(date=today)
This should prevent multi-shot analysis from slowing down when lyse is not restarted often.