The inputed spatial transcriptomics data is only available in log2 transformed form. Some downstream analysis requires normalized data. What is the best way of doing this? Can I get back to the raw counts by 2^(log2 values)?
Hi @wykpenguin ,
According to the scientists who did this analysis from the original publication:
“We used the log normalized value (y) in the imputation, which is log2(CPM + 1), where CPM = (10^6 /sample_count_sum) * rawcount. Imputation takes a knn average of these values. So the exact reverse engineering of rawcount = ( sample_count_sum / 10^6) \*(2^y - 1) won’t be feasible. Since we are taking knn averaging, using rawcounts might not be desirable, [and] we don’t have the rawcount for Merfish data.”
If you need additional information, please reply to this thread.