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qtl2fst vs sdsfun

A side-by-side editorial comparison of qtl2fst and sdsfun — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r-package

qtl2fst vs sdsfun: at a glance

Featureqtl2fstsdsfun
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesr-package, genetics, memory-efficiency, on-disk-storagespatial-statistics, geodetector, spatial-clustering, rcpp
Last editorial update4h ago1h ago
WebsiteVisit →Visit →

What is qtl2fst?

The out-of-memory backend for R/qtl2, feature-complete since 2020 and now purely on upkeep

qtl2fst backs R/qtl2 genotype probabilities with on-disk fst files so large crosses don't have to fit in RAM. Its defining release was 0.22 in 2020, which added calc_genoprob_fst() and genoprob_to_alleleprob_fst() to fuse calculation and storage in one step. The five releases since are documentation links, directory-creation robustness, a Windows example fix, and — in 0.32 — a change to how cores=0 is interpreted.

Read the full qtl2fst trajectory →

What is sdsfun?

A spatial-statistics utility package exists to be depended on, and is built accordingly.

sdsfun collects spatial data science utilities — neighbour lists, spatial constrained clustering, discretization, dummy variable generation, geographical detector statistics and projection helpers — with the computationally heavy parts implemented in Rcpp. It was assembled quickly across late 2024, adding a function set roughly every three weeks, and has slowed since to a couple of releases a year. The most recent work is corrective: no longer initializing the RNG state at load, fixing matrix inputs misread as vectors, and clearing an Armadillo deprecation.

Read the full sdsfun trajectory →

qtl2fst vs sdsfun: editorial side-by-side

Q
qtl2fst
ANALYTICS
0.0

The out-of-memory backend for R/qtl2, feature-complete since 2020 and now purely on upkeep

◆ Current state

qtl2fst backs R/qtl2 genotype probabilities with on-disk fst files so large crosses don't have to fit in RAM. Its defining release was 0.22 in 2020, which added calc_genoprob_fst() and genoprob_to_alleleprob_fst() to fuse calculation and storage in one step. The five releases since are documentation links, directory-creation robustness, a Windows example fix, and — in 0.32 — a change to how cores=0 is interpreted.

◆ Where it's heading

The package has settled into the role of a stable satellite of R/qtl2: it tracks the parent package's conventions rather than setting its own. The cores=0 change in 0.32 arrived alongside the identical change in qtl2convert, so the parallel-computing default is being standardized across the maintainer's packages at once. Release intervals have stretched from months to years.

◆ Prediction

Further releases will most likely mirror changes originating in R/qtl2 or CRAN checks, in the same follow-the-parent pattern as 0.24 and 0.32.

S
sdsfun
ANALYTICS
0.0

A spatial-statistics utility package exists to be depended on, and is built accordingly.

◆ Current state

sdsfun collects spatial data science utilities — neighbour lists, spatial constrained clustering, discretization, dummy variable generation, geographical detector statistics and projection helpers — with the computationally heavy parts implemented in Rcpp. It was assembled quickly across late 2024, adding a function set roughly every three weeks, and has slowed since to a couple of releases a year. The most recent work is corrective: no longer initializing the RNG state at load, fixing matrix inputs misread as vectors, and clearing an Armadillo deprecation.

◆ Where it's heading

This is infrastructure for a family of packages rather than an end-user tool, and the changelog says so directly — functions were added to support gdverse and sesp, and moran_test was migrated in from geocomplexity. That migration pattern is the defining move: capability consolidates here so the downstream packages can share it instead of each carrying its own copy. Growth has slowed as that consolidation completed, leaving correctness and dependency upkeep.

◆ Prediction

Given the package moves when its dependents need something, the next release most likely brings in another shared function or responds to a downstream requirement rather than following its own plan. Armadillo and CRAN check changes remain the reliable source of maintenance work.

Alternatives to qtl2fst and sdsfun

Other Analytics 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 qtl2fst or sdsfun.

See all qtl2fst alternatives → · See all sdsfun alternatives →

Recent activity from qtl2fst and sdsfun

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

  1. 1mo agoqtl2fstcores=0 now leaves one core free instead of taking all
  2. 10mo agosdsfunPackage load stops touching the RNG state
  3. 1y agosdsfunUnified partial correlation testing and head/tails discretization
  4. 1y agosdsfunMissing-value handling added to linear trend removal
  5. 1y agosdsfunCovariate-based detrending and long-to-matrix spatial reshaping
  6. 1y agosdsfunSpatially constrained hierarchical clustering and SPADE estimation
  7. 1y agoqtl2fstWindows fix for the replace_path() example
  8. 1y agosdsfunFast geodetector q-value estimator added
  9. 2y agoqtl2fstDocumentation link fix
  10. 4y agoqtl2fstCreates missing directories instead of erroring out
  11. 5y agoqtl2fstTest coverage for qtl2 functions against fst-backed probabilities
  12. 6y agoqtl2fstDocumentation and metadata cleanup for CRAN

Frequently asked questions

What is the difference between qtl2fst and sdsfun?

Both compete on the same themes — r-package — within Analytics. qtl2fst and sdsfun 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 qtl2fst better than sdsfun?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. qtl2fst and sdsfun 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 Analytics products to evaluate alongside.

What are the best alternatives to qtl2fst?

Top qtl2fst alternatives in Analytics are ranked by recent ship velocity. Browse the "qtl2fst alternatives" section above for the current picks, or visit /alternatives/qtl2fst for the full list with editorial commentary on each.

What are the best alternatives to sdsfun?

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