tinyi
commented
4 years ago Dear Kristoffer,
Thank you very much for your feedback.
In theory, Mistake 1 should not happen, as TED allows all zero genes in the input, which will not affect the result. It would help if you can provide me a subset of your samples that generates the error, so I may troubleshoot and make sure the outputs are correct.
I will add assertions/alerts to prevent mistake 2 and 3 in the next updates.
Best,
Tinyi
On Fri, Feb 21, 2020 at 4:40 AM Kristoffer Vitting-Seerup < notifications@github.com> wrote:
I've been using run.Ted a few times now and I've made a couple observations which results in TED giving uninformative error message. These should be easy for you to implement small test to prevent other people from making the same (stupid) mistakes as me.
Mistake 1: Having gene(s) with all zeros (I think). I had a bulk dataset which gave this error:
[1] "inferred cell percentage" [1] "correct batch effect" [1] "every gene has at least one zero. vst transformation is NOT feasible" [1] "run final sampling" Error: $ operator is invalid for atomic vectors In addition: Warning message: In mclapply(1:N, FUN = function(i) { : all scheduled cores encountered errors in user code
After I filtered the data to remove genes with only zeroes the run went fine.
Mistake 2:
The second is that due to a typo I tried running with a data.frame which had NAs in - this also cause TED to fail with an uninformative error message - and took a while to figure out.
Mistake 3: I make a spelling mistake causing my logic argument to retun an empty vector to be used with the tum.idx argument which naturally caused TED to fail with an uninformative error message
Guess the morale is don't underestimate how strange things users can do :)
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ThomasJamesMitchell
I've been using
run.Teda few times now and I've made a couple observations which results in TED giving uninformative error message. These should be easy for you to implement small test to prevent other people from making the same (stupid) mistakes as me.Mistake 1: Having gene(s) with all zeros (I think). I had a bulk dataset which gave this error:
After I filtered the data to remove genes with only zeroes the run went fine.
Mistake 2:
The second is that due to a typo I tried running with a data.frame which had NAs in - this also cause TED to fail with an uninformative error message - and took a while to figure out.
Mistake 3: I make a spelling mistake causing my logic argument to retun an empty vector to be used with the
tum.idxargument which naturally caused TED to fail with an uninformative error messageGuess the morale is don't underestimate how strange things users can do :)