All Rcm values are less than 1

[Joyjoyjoyc]

Hi there,
thanks for developing such a useful tool, I wonder if all Rcm values are less than 1, does it mean receivers are less likely to be sufficiently included in the input mixed cells. So when running this script, MTreceiver_pre <- MERCI_ReceiverPre(DNA_rank, RNA_rank, top_rank=50), which parameter should I set for top_rank? and is the result usable? Thank you so much!

[shyhihihi]

In this case, since all Rcm < 1, it seems that no sufficient receivers are included in your input mixed cells. You may also want to check the p-values and FDR values. If none are significant for any top-ranked cutoff, it is likely that this sample is not suitable for calling receivers.
Typically, we conduct tests on a sample-by-sample basis. Usually, ~3 samples can be detected with receivers among 10 samples when using the Rcm test. Perhaps you could consider testing samples from other individuals.
Notably, MERCI is a conserved method for testing receiver existence. Some actual receivers may not be detected when the donor-derived MT fraction is low. We cannot conclude that MT transfer does not occur even when all Rcm < 1. However, we still recommend excluding this sample.

[Joyjoyjoyc]

In this case, since all Rcm < 1, it seems that no sufficient receivers are included in your input mixed cells. You may also want to check the p-values and FDR values. If none are significant for any top-ranked cutoff, it is likely that this sample is not suitable for calling receivers. Typically, we conduct tests on a sample-by-sample basis. Usually, ~3 samples can be detected with receivers among 10 samples when using the Rcm test. Perhaps you could consider testing samples from other individuals. Notably, MERCI is a conserved method for testing receiver existence. Some actual receivers may not be detected when the donor-derived MT fraction is low. We cannot conclude that MT transfer does not occur even when all Rcm < 1. However, we still recommend excluding this sample.

Hi @shyhihihi, thanks for your reply! I still wonder how can I check the p-values and FDR values. As I followed every step of the tutorial rigorously and didn't find anywhere to view the p-values and FDR values. Thank you so much!

[shyhihihi]

You can check p values and FDR in the output variable of 'CellNumber_test' function.