Closed peneder closed 5 years ago
Hi @peneder
Thank you for your interest in ichorCNA.
The lines represent segment medians. If it is the same color as the dots, then it is predicted to the clonal. If it is light green, then it is predicted to be subclonal. This is made a bit clearer in the wiki (https://github.com/broadinstitute/ichorCNA/wiki/Output)
There are 2 potential issues with the results you have attached.
--includeHOMD False
. The reason is that large homozygous deletions are typically less likely (unless you have reason to believe that is the case) and that this will help with selecting the appropriate ploidy solution.--fracReadsInChrYForMale
threshold is not set appropriately for your data. If the fraction of coverage in chrY is higher than this value, then it will be called "male". You can look at the params.txt
file to check this fraction for each sample. Then, set this value such that it your samples will meet the threshold.
b. you are using a matched normal sample that is female.
c. the sex/gender of the samples in the panel of normals are also called incorrectly. You should take a look at the chrX values in the PoN to make sure that they have log ratio close to 0. Hi! Thanks for the answer and sorry for the long silence on my side. It would be great if you could help me with these two further questions.
You said that light green lines represents subclonality. But what do light green dots mean? They are not mentioned in the wiki. Is it possible that they represent homozygous deletions?
I cannot figure out why the X chromosome is not placed at the log ratio of zero. The readcounts countain X and Y chromosomes. Interestingly, when I check the params.txt files for the male samples, they are all recognized as male. I am using the panel of normals that comes with ichor (/inst/extdata/HD_ULP_PoN_hg38_500kb_median_normAutosome_median.rds". Is this panel not compatible to use with male samples? I also tried using no normalization at all, but that did not give adequate results, as did using a single negative control sample. Thanks for your help!
Hi @peneder
You said that light green lines represents subclonality. But what do light green dots mean? They are not mentioned in the wiki. Is it possible that they represent homozygous deletions? Yes, you are correct. Bright green = homozygous deletions
I cannot figure out why the X chromosome is not placed at the log ratio of zero. The readcounts countain X and Y chromosomes. Interestingly, when I check the params.txt files for the male samples, they are all recognized as male. I am using the panel of normals that comes with ichor (/inst/extdata/HD_ULP_PoN_hg38_500kb_median_normAutosome_median.rds". Is this panel not compatible to use with male samples? I also tried using no normalization at all, but that did not give adequate results, as did using a single negative control sample.
Again, this is not expected behavior of ichorCNA, especially if it is indicating male
in the params.txt
file. That panel should work for both female and male samples. Are you sure that you the argument --normalizeMaleX
is set to TRUE
?
posted a query in google groups which includes the problem mentioned by @peneder as well
https://groups.google.com/a/broadinstitute.org/d/topic/ichorcna/wYddw8Nwegs/discussion
Hi! In some of the plots that I generated using ichorCNA, some regions are marked as "3 copies" (brown dots) or "1 copy" (dark (!) green dots) and have a bright green line. I assume this means that the subclonal fraction of the tumor is predicted to have 3 or 1 copies of this segment, respectively, whereas the rest of the tumor has 2 copies. My confusion comes from the following: Sometimes I have observed regions that have bright green dots with a bright green line. What does it mean? Sometimes the different sub-solutions show the same segment either with dark green dots and a bright green line, or with bright green dots and a bright green line. Similarly, sometimes they show a segment either with dark green dots and a dark green line, or with bright green dots and a bright green line. These differences seem to heavily influence the prediction of the tumor fraction in some cases. Could you please explain why that is and maybe add the explanation to the wiki? Thank you!