Description Usage Arguments Value Note
View source: R/annotation_analysis.R
This function takes MPRA data and an annotation source (or alternatively pre-fit priors) and checks how well the conditional prior improves upon the marginal prior by a prior ratio at the maximum likelihood estimates. A conditional:marginal ratio > 1 indicates that the conditional prior does better. A higher fraction of alleles for which this is true indicates an improved conditional prior.
1 2 3 4 5 6 7 | score_annotation(
mpra_data,
annotations,
nb_params = NULL,
conditional_prior = NULL,
marginal_prior = NULL
)
|
mpra_data |
a data frame of MPRA data |
annotations |
a data frame containing annotations of the same alleles in mpra_data |
nb_params |
an optional data frame of pre-fit maximum likelihood estimates for allele parameters |
conditional_prior |
an optional data frame containing pre-fit conditional priors |
marginal_prior |
an optional data frame containing a pre-fit marginal prior |
A fraction between 0 and 1 indicating the number of parameter estimates that have higher density under the conditional prior than under the marginal prior.
Note that even with near-perfect annotations or conditional priors, the fraction of parameter estimate ratios above 1 will not approach 1. It will instead approach some difficult-to-determine limit defined by the noise in the assay. Thus this functionality should only be used to COMPARE annotation sources, rather than make discrete claims / measurements about individual annotation sources.
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