GWW
commented
1 year ago It's more likely that the mutations are poorly covered by the 10X library. Depending on the library type the reads are clustered towards a few hundred basepairs near the 5'- and 3'- end of a transcript. Most of the coverage ends up being in the UTR and first/last exon. Occasionally, you may get lucky and a mutation will be close to an intronic poly(A) site in 3'- libraries, which leads to some coverage of the mutation. You can always check your alignment files in IGV and see if there is any coverage in your region of interest. It's also important to have relatively high sequencing saturation when mutation calling as this will maximize the amount of coverage from each collapsed read.
ttt-404
Hi, I analyzed serveal samples using scSNV and annotated mutations using ANNOVAR to find high-frequency mutated genes in cancer. However, I found that the results did not support the conclusions in bulk data. There’s no much mutations detected in cancer related genes like TP53, PTEN or DAXX (0% ~ 2% in 30000 cancer cells, but they did expressed). I think it's too strange, do you have any idea of this? Is it due to the sparsity of 10x data?
Thank you so much!