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na.omit wiping out data.table #2
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Hello @tlesluyes. |
Hi @asd1289, Actually, the function works well until line 679 because I do have Here is the code I use to decompose my normal sample and where I end up with NAs (is the mc.cores useful as it's not explicitely used in the function?):
EDIT |
I have the same issue. WES analysis. Everything works till the germline events identification step which fails and gives the following error:
I do have drycleaned normals and NA value appears there as well:
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Hello @tlesluyes and @kcygan thanks for pointing out this bug. I am working on this and will push a patch asap. |
Thanks a lot @asd1289 When you push the changes could you please also update the start_wash_cycle function, line 694 from |
@kcygan I have changed that typo. Please stay tuned for the NA error. |
I'm having a similar error when using
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@tlesluyes @kcygan @willhooper I have added a temporary fix as suggested by @tlesluyes for now. I am keeping this issue open to follow up on this bug. Please let me know of additional issues. Thank you for reporting bugs and take care! |
Hi. I have an issue using the
identify_germline
function, wherena.omit
(dryclean.R#L310) destroys my entire data.table (0 lines = 0 samples). My understanding is thatna.omit
removes the entire line (corresponding to a sample) if it finds any NA value. But you do have NA values in there using WGS because of low-complexity regions, telomeres, centromeres, etc. Typically, my first positions correspond to chr1 telomere where I don't have any mapped read. Shouldn't it remove columns instead (corresponding to a genomic window where a single sample has a NA value? Aren't lines 310 and 311 inverted (transpose the data.table and then remove NA regions)?The text was updated successfully, but these errors were encountered: