Changes in version 1.0.2                        

  - Added a standalone vignette (html file)

                        Changes in version 1.0.1                        

  - Additive update. Two new exported functions plus documentation
    clarifications.

  - New functions

collapseToGenets(dataset, genetAssignment, representative,
drop_unassigned) Reduces a genotype data frame to one representative
colony per genet, using genet assignments from runGenets(). Picks the
most-complete colony per genet (lowest pctNull) by default; keeps
unassigned/inadequate colonies as individuals unless drop_unassigned =
TRUE. Matches rows on Coral_ID, so identifiers may contain any
characters. Pure row filter — genotype values are untouched.

computeKinship(data, subset, targetN) Data-frame entry point to the
kinship pipeline — the in-memory counterpart to runKinship() (no
Data/Results folders). Runs the same internal steps (translate to IUPAC
codes, set aside all-NA colonies, omit invariant loci, compute kinship)
and returns the same PopAvgMKGD / MK_init / MK_final list, keyed by
Coral_ID. Verified to return results identical to runKinship() on the
same data. Errors informatively if Coral_ID is missing or if the input
is single-letter coded data rather than paired alleles.

  - Together these enable clone-corrected diversity in one line

eligible-pool diversity (all colonies, ramets included):
computeKinship(raw) clone-corrected (one colony per genet): ga <-
runGenets(PctMatchThreshold = 90, PctNotNullThreshold
= 50)$genetAssignments[[1]] computeKinship(collapseToGenets(raw, ga))

                        Changes in version 1.0.0                        

  - initial release