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Hello, thank you very much for developing this great tool!
I have encountered an issue with the processing of a sample, (I already know it is a problematic sample since the start. During the sample preparation there were some loading issue).
Specifically, the autoEstCont suggest an Extremely high rho.
sc1 <- autoEstCont(sc)
5380 genes passed tf-idf cut-off and 2448 soup quantile filter. Taking the top 100.
Using 583 independent estimates of rho.
Estimated global rho of 0.63
Error in setContaminationFraction(sc, contEst, forceAccept = forceAccept) :
Extremely high contamination estimated (0.63). This likely represents a failure in estimating the contamination fraction. Set forceAccept=TRUE to proceed with this value.
The run fails. This is the distribution of the estimated rho(s).
I have two options, and I am not sure which one is more appropriate.
I have tried to use the setContaminationFraction based on the distribution from the failed autoEstCont call, and set a manual value of 0.1 which is roughly the center of the first peak.
I have tried to use the contaminationRange argument in autoEstCont and reduced the total range for the estimates
sc4 <- autoEstCont(sc,contaminationRange = c(0.01,0.5))
5380 genes passed tf-idf cut-off and 2448 soup quantile filter. Taking the top 100.
Using 267 independent estimates of rho.
Estimated global rho of 0.06
The run does not fail. This is the result distribution of the estimated rho(s).
I was wondering:
a) Does it make sense to force a manual rho in this case, or would you discard the sample?
b) Would you suggest approach 1 or 2? I have noticed that the distribution of approach 2 is different from the failed run of autoEstCont.
The text was updated successfully, but these errors were encountered:
pedriniedoardo
changed the title
SoupX high contamination rate guideline
SoupX high contamination guideline
Apr 19, 2024
Hello, thank you very much for developing this great tool!
I have encountered an issue with the processing of a sample, (I already know it is a problematic sample since the start. During the sample preparation there were some loading issue).
Specifically, the
autoEstCont
suggest an Extremely high rho.The run fails. This is the distribution of the estimated rho(s).
Now, I was trying to follow the recommendation suggested by @constantAmateur here #60 (comment)
I have two options, and I am not sure which one is more appropriate.
setContaminationFraction
based on the distribution from the failedautoEstCont
call, and set a manual value of 0.1 which is roughly the center of the first peak.contaminationRange
argument inautoEstCont
and reduced the total range for the estimatesThe run does not fail. This is the result distribution of the estimated rho(s).
I was wondering:
a) Does it make sense to force a manual rho in this case, or would you discard the sample?
b) Would you suggest approach 1 or 2? I have noticed that the distribution of approach 2 is different from the failed run of
autoEstCont
.The text was updated successfully, but these errors were encountered: