BeviMed 5.1
- New function,
subset_variants
, which retains only
variants with data bearing upon pathogenicity.
- Return posterior mean of
omega
even when not explicitly
sampled in summary.BeviMed_m
.
BeviMed 5.0
bevimed_polytomous
function added which enables
application of BeviMed across multiple association models.
BeviMed
objects now more general, representing results
of inference with respect to the baseline model gamma = 0
and an arbitrary number of alternative association models - typically,
one for each mode of inheritance. The $moi
slot has been
replaced with $models
.
prob_pathogenic
now returns a list when broken down by
mode of inheritance/model.
BeviMed 4.3
- Make BeviMed work smoothly when number of individuals or number of
variants is 0.
- Retain names of variants from columns of original allele count
matrix.
- Improvements to guide, with more detail on model selection.
BeviMed 4.2
- Fixed bug in calculation of expected number of explaining variants
by only including those with pathogenic configurations.
BeviMed 4.0
- Previous
bevimed
function now replaced by
bevimed_m
, with the _m
indicating that it
conditions on mode of inheritance.
bevimed
now integrates over indicator of association
(gamma) and mode of inheritance (m), allowing user to specify priors on
probability of association and probability of dominance.
- The
BeviMed
class object has been replaced by
BeviMed_m
, and a new BeviMed
class has been
introduced for inference with respect to all models: gamma 0 and gamma 1
under each mode of inheritance.
- A new vignette with more detail called
BeviMed Guide
which relates the package to the paper.
- Names used for summary statistics in summary objects have changed,
see function help pages for details on current names.
print
ing a BeviMed
object now shows
conditional probabilities of pathogenicity for each mode of inheritance,
and expected explained cases and expected explaining variants shown
too.
- Bug fixed in adaptive tuning for omega and phi proposals.
BeviMed 3.0
- Re-naming of parameters in
bevimed
function to match
the names of variables in the paper (under submission).
- The allele count matrix
G
should now be supplied as a
matrix with rows corresponding to individuals, not variants.
expected_explained
and explaining_variants
functions have been added, respectively computing the expected number of
cases with their disease explained by the given variants, and expected
number of pathogenic variants present amongst cases.