I came across rMATS while doing research on differential alternative splicing (AS). It uses logit-normal distibution to model variation among biological replicates. I am having difficulty understanding the logics here.
Can anyone share some insights on how logit-normal distribution can model such variation? It does not have to be AS specific as long as the allow me to understanding the rational here.
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written
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CY
1 answer
It says, in the paper:
rMATS uses a binomial distribution to model the read count from the exon inclusion isoform given the exon inclusion level in each individual replicate and a logit-normal distribution to model the variation among replicates within sample group.
This is a big assumption that likely does not hold for all genes, which is a limitation of rMATs. I guess that they mean, that, if you plot the read counts for every exon over every identified isoform, then it would follow a binomial. Exons that are only expressed in rare isoforms would be at either tail of the curve.
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