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Bootstrap resampling, if we have enough samples. Do we? We can calculate the bootstrapped confidence interval for the log2 fold change of the category means or medians.
Bootstrap using kallisto/salmon/sailfish bootstraps, but here we also need to aggregate the bootstrap values across samples. In the previous method, the bootstrap refers to drawing random samples, while here we draw random sets of reads (kind of) for each sample. Use bootstrap values to calculate a 95% CI for the differential diversity results.
Beta regression with a likelihood ratio or Wald-test using the normalized entropy values. Stg like entropy ~ condition + tpm | tpm vs entropy ~ tpm | tpm if we want to take into account the effect of gene expression on entropy.
The text was updated successfully, but these errors were encountered:
Additional ways to calculate significance later:
entropy ~ condition + tpm | tpm
vsentropy ~ tpm | tpm
if we want to take into account the effect of gene expression on entropy.The text was updated successfully, but these errors were encountered: