vafClust | R Documentation |
Suppose we have read coverage over a base with a detected variant. We can model the reads mapping to variant and reference bases as
vafClust(alt, ref, depth = NULL, ...)
alt |
read depth for the variant allele |
ref |
read depth for the reference allele |
... |
additional arguments to pass on to dbscan |
eps |
epsilon to use for DBSCAN clustering |
p ~ Beta(variant_reads, reference_reads)
Now, if we take logits, with nu = logit(p), then
nu ~ Normal( log(p/(1-p)), log10(total reads) )
As a bonus, we can model nu
as roughly multivariate normal.
Furthermore, we can use the latter term as observation weights.
Given a vector or matrix of VAFs, this function clusters them
using dbscan, with log10(read_depth) as the weight for each VAF.
an object of class `dbscan_fast`
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