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Comparison · Infra & APIs

driveR vs fdacluster

A side-by-side editorial comparison of driveR and fdacluster — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r-package

driveR vs fdacluster: at a glance

FeaturedriveRfdacluster
SectorInfra & APIsInfra & APIs
Velocity score0.00.0
Sparks · 30d00
Top themescancer-genomics, bioinformatics, r-package, driver-genesfunctional-data-analysis, clustering, r-package, rcpp
Last editorial update1h ago1h ago
WebsiteVisit →Visit →

What is driveR?

A cancer driver prioritization package that ships rarely and mostly to stay installable

driveR prioritizes cancer driver genes from somatic variant and copy number data, combining coding impact scores, noncoding impact, copy number alteration scores and hotspot annotations into a multi-task learning classification model. Version 0.5.0 added gene-level SCNA data frames as an accepted input to create_features_df(), with an example table shipped alongside, widening the entry point beyond the segment-level format. The same release moved org.Hs.eg.db and both hg19 and hg38 TxDb annotation packages from Imports to Suggests under new CRAN policy, with dependent functions now raising an error when they are absent rather than silently degrading.

Read the full driveR trajectory →

What is fdacluster?

Functional data clustering grew from one algorithm into a comparable suite

fdacluster clusters functional data while separating amplitude from phase variation, aligning curves as part of the clustering rather than before it. The algorithm set covers k-means, hierarchical clustering and DBSCAN, all producing a common caps result object so runs can be compared directly. Version 0.4.0 tightened the interface with is_domain_interval and transformation arguments describing the input data, added compatibility checking between incompatible option combinations, and split the L2 and normalized L2 distances into separate C++ classes to enforce that plain L2 cannot be combined with dilation or affine warping it is not invariant to.

Read the full fdacluster trajectory →

driveR vs fdacluster: editorial side-by-side

D
driveR
INFRA · APIS
0.0

A cancer driver prioritization package that ships rarely and mostly to stay installable

◆ Current state

driveR prioritizes cancer driver genes from somatic variant and copy number data, combining coding impact scores, noncoding impact, copy number alteration scores and hotspot annotations into a multi-task learning classification model. Version 0.5.0 added gene-level SCNA data frames as an accepted input to create_features_df(), with an example table shipped alongside, widening the entry point beyond the segment-level format. The same release moved org.Hs.eg.db and both hg19 and hg38 TxDb annotation packages from Imports to Suggests under new CRAN policy, with dependent functions now raising an error when they are absent rather than silently degrading.

◆ Where it's heading

Releases are infrequent and split cleanly between capability and correction. GRCh38 support arrived in 0.4.0 and cancer-type-specific thresholds were refreshed in 0.3.0, while the 0.2.x pair fixed scoring errors serious enough to require retraining: a column name mismatch meant the SCNA score was not being computed at all, and MCR table coordinates needed converting from hg18 to hg19. Both times the bundled classification model and thresholds were rebuilt as a consequence. Since 0.4.0 the changes have been input handling and packaging rather than method.

◆ Prediction

The move of the annotation databases to Suggests suggests a leaner install is the current priority; the entries give no indication of planned model or scoring changes.

F
fdacluster
INFRA · APIS
0.0

Functional data clustering grew from one algorithm into a comparable suite

◆ Current state

fdacluster clusters functional data while separating amplitude from phase variation, aligning curves as part of the clustering rather than before it. The algorithm set covers k-means, hierarchical clustering and DBSCAN, all producing a common caps result object so runs can be compared directly. Version 0.4.0 tightened the interface with is_domain_interval and transformation arguments describing the input data, added compatibility checking between incompatible option combinations, and split the L2 and normalized L2 distances into separate C++ classes to enforce that plain L2 cannot be combined with dilation or affine warping it is not invariant to.

◆ Where it's heading

The trajectory runs from method implementation toward guardrails and portability. Early releases added capability; recent ones prevent misuse and reduce weight - dplyr, forcats, tidyr and purrr removed in 0.4.0, furrr swapped for future.apply - while 0.4.2 is entirely C++ correctness, replacing Armadillo's whole-object finiteness check with scalar std::isfinite and fixing an integer overflow in linear index computation that broke large datasets. Cadence is roughly one release a year.

◆ Prediction

Given that the last two releases were dependency reduction and numerical correctness rather than method work, expect the next to continue in that vein unless a new clustering algorithm is contributed.

Alternatives to driveR and fdacluster

Other Infra & APIs products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either driveR or fdacluster.

See all driveR alternatives → · See all fdacluster alternatives →

Recent activity from driveR and fdacluster

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 7mo agofdaclusterInteger overflow fixed for large datasets, C++ finiteness checks corrected
  2. 7mo agodriveRGene-level copy number input accepted, annotation packages made optional
  3. 1y agofdaclusterParallel worker setup and an acronym correction
  4. 1y agofdaclusterInput description arguments and enforced distance-warping compatibility
  5. 3y agodriveRCRAN documentation error fixed
  6. 3y agofdaclusterMedian centroids and centroids defined on unioned grids
  7. 3y agofdaclusterNamespace notation and optional dependency guards
  8. 3y agofdaclusterHierarchical clustering, DBSCAN and a shared result class arrive together
  9. 4y agodriveRGRCh38 genome build supported
  10. 4y agodriveRCancer-type-specific thresholds updated
  11. 5y agodriveRMCR coordinates converted to hg19 and the model retrained
  12. 5y agodriveRCopy number score was never being computed, model rebuilt

Frequently asked questions

What is the difference between driveR and fdacluster?

Both compete on the same themes — r-package — within Infra & APIs. driveR and fdacluster are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.

Is driveR better than fdacluster?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. driveR and fdacluster are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Infra & APIs products to evaluate alongside.

What are the best alternatives to driveR?

Top driveR alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "driveR alternatives" section above for the current picks, or visit /alternatives/driver for the full list with editorial commentary on each.

What are the best alternatives to fdacluster?

Top fdacluster alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "fdacluster alternatives" section above for the current picks, or visit /alternatives/fdacluster for the full list with editorial commentary on each.