A collection of high-performance methods for computing distance
measures for bioinformatics data. The weighted Euclidean distance can be
computed using 'OpenCL' on a GPU or a parallelized implementation on a CPU.
Other important distance measures for bioinformatics data are provided by
the R package 'parallelDist'. A specialized distance measure for the Gene
Ontology is also available.
| Version: |
0.1.5 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
Rcpp (≥ 1.0.8), RcppParallel, parallelDist, parallel, DataVisualizations, diptest, e1071, vegan, methods, pracma, ggplot2 |
| LinkingTo: |
Rcpp, RcppParallel, RcppArmadillo |
| Suggests: |
knitr, rmarkdown, remotes, sphet, OpenCL, transport, ineq, memshare, philentropy (≥ 0.10.0), manydist (≥ 0.5.0) |
| Published: |
2026-08-04 |
| DOI: |
10.32614/CRAN.package.BIDistances |
| Author: |
Quirin Stier 
[aut, rev, ctb],
Michael Thrun
[aut, cre],
Luca Brinkmann [ctb] |
| Maintainer: |
Michael Thrun <m.thrun at gmx.net> |
| BugReports: |
https://github.com/Mthrun/BIDistances/issues |
| License: |
GPL-3 |
| NeedsCompilation: |
yes |
| SystemRequirements: |
GNU make, OpenCL library (optional, for GPU
acceleration), pandoc (>=1.12.3, needed for vignettes) |
| Citation: |
BIDistances citation info |
| CRAN checks: |
BIDistances results [issues need fixing before 2026-08-21] |