abyzovlab / CNVpytor

a python extension of CNVnator -- a tool for CNV analysis from depth-of-coverage by mapped reads
MIT License
178 stars 26 forks source link

cnvpytor.utils - WARNING - Problem with fit: Runtime Error. Using mean and std instead fitting parameters! #174

Open kaqisekuzi opened 1 year ago

kaqisekuzi commented 1 year ago
          Hi @suvakov 

I sent the log file to your email. Below is the Manhattan plot of the two samples. Does this Manhattan plot have anything to do with the warning message?

warning message: cnvpytor.utils - WARNING - Problem with fit: Runtime Error. Using mean and std instead fitting parameters!

log file: sample_3964_And_sample_4352.log.txt

22S04403964 manhattan global 0000 22S04404352 manhattan global 0000

Originally posted by @kaqisekuzi in https://github.com/abyzovlab/CNVpytor/issues/171#issuecomment-1491467672

kaqisekuzi commented 1 year ago

Hi @suvakov @abyzov Does this Manhattan plot have anything to do with the warning message? warning message: cnvpytor.utils - WARNING - Problem with fit: Runtime Error. Using mean and std instead fitting parameters!

suvakov commented 1 year ago

Warning message is expected due to shallow coverage (around 1x according to log files) and it is not related to Manhattan plot. Is this cancer sample (first plot)?

Thanks, Milovan

kaqisekuzi commented 1 year ago

@suvakov Yes , first plot is a cancer sample. Do these warnings have any effect on my results? Is it possible to ignore these warning messages?

Thanks, kaqisekuzi

suvakov commented 1 year ago

You can safely ignore warning messages. In the first example, it's unclear what copy number 2 level refers to. Normalization is typically performed based on the mean level of autosomes, but in cancer cases, this may differ from the actual copy number 2. Our 2D caller addresses this issue by using only diploid regions for normalization based on B-allele frequency (BAF). However, this approach may not be applicable here due to the low coverage. My suggestion is to manually normalize the levels by assuming that the beginning of chromosome 1 (or any other region where you believe it is most likely to have 2 copies) has a copy number of 2.