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discretefdr vs mmconvert

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

Shared themes:r-package

discretefdr vs mmconvert: at a glance

Featurediscretefdrmmconvert
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesmultiple-testing, false-discovery-rate, discrete-statistics, r-packager-package, genetics, genome-build, reference-data
Last editorial update1h ago36m ago
WebsiteVisit →Visit →

What is discretefdr?

The discrete-data FDR package is being pared into one piece of a larger multiple-testing suite.

DiscreteFDR implements false discovery rate procedures adapted for discrete test statistics, where the standard continuous-case corrections are conservative. It now covers a discrete Benjamini-Yekutieli procedure alongside the Benjamini-Hochberg variants it started with, including adaptive versions. Its datasets and test-result classes have been moved out into companion packages, so it increasingly does one job and defers the rest.

Read the full discretefdr trajectory →

What is mmconvert?

A single-purpose mouse map interpolator that solved its problem in 2023 and has coasted since

mmconvert does one thing: interpolate between GRCm39 physical positions and the revised Cox genetic map for mouse MUGA array markers. The substantive work all landed in a burst across 2021-2023 — the initial function, the GRCm39 annotation dataset, cross2_to_grcm39(), the recomputed Cox maps and their smoothed replacement. Everything since is upkeep: a warning-message fix in 0.12, and 0.14 is a test adjustment to silence a CRAN Note with no code change at all.

Read the full mmconvert trajectory →

discretefdr vs mmconvert: editorial side-by-side

D
discretefdr
ANALYTICS
0.0

The discrete-data FDR package is being pared into one piece of a larger multiple-testing suite.

◆ Current state

DiscreteFDR implements false discovery rate procedures adapted for discrete test statistics, where the standard continuous-case corrections are conservative. It now covers a discrete Benjamini-Yekutieli procedure alongside the Benjamini-Hochberg variants it started with, including adaptive versions. Its datasets and test-result classes have been moved out into companion packages, so it increasingly does one job and defers the rest.

◆ Where it's heading

The direction is decomposition into a suite. The amnesia dataset went to DiscreteDatasets, summary output now interoperates with the DiscreteTestResults class from DiscreteTests, and match.pvals() stopped being exported — each release trims something that belongs elsewhere. What remains gets methodological additions at a slow, deliberate cadence, with performance work on the step-up procedures that dominate cost when the number of tests is large. Recent activity is maintenance: replacing deprecated calls the package still made of its own siblings. This is a mature statistical package whose release notes are short because the methods underneath them are settled.

◆ Prediction

Expect further alignment with the companion packages rather than new procedures, since the last substantive release was already about interoperating with DiscreteTests classes and the most recent one about clearing deprecations.

M
mmconvert
ANALYTICS
0.0

A single-purpose mouse map interpolator that solved its problem in 2023 and has coasted since

◆ Current state

mmconvert does one thing: interpolate between GRCm39 physical positions and the revised Cox genetic map for mouse MUGA array markers. The substantive work all landed in a burst across 2021-2023 — the initial function, the GRCm39 annotation dataset, cross2_to_grcm39(), the recomputed Cox maps and their smoothed replacement. Everything since is upkeep: a warning-message fix in 0.12, and 0.14 is a test adjustment to silence a CRAN Note with no code change at all.

◆ Where it's heading

The package has reached the natural end state of a reference-data converter — the reference data stopped moving, so the package stopped moving. Releases now arrive roughly annually and exist to keep CRAN checks green. The 0.14 release shipped the same day as sibling qtl2convert 0.36, confirming these are batch maintenance passes across the maintainer's packages rather than independent development.

◆ Prediction

Without a new mouse genome build or a revised Cox map, the next release is likely another CRAN-check accommodation rather than new functionality.

Alternatives to discretefdr and mmconvert

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 discretefdr or mmconvert.

See all discretefdr alternatives → · See all mmconvert alternatives →

Recent activity from discretefdr and mmconvert

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

  1. 1mo agommconvertTest adjustment to clear a CRAN Note
  2. 3mo agodiscretefdrDeprecated internal calls replaced
  3. 1y agommconvertFixes a malformed warning message in mmconvert()
  4. 1y agodiscretefdrDiscrete Benjamini-Yekutieli procedure added
  5. 1y agodiscretefdrDatasets split out and step-up procedures sped up
  6. 3y agommconvertOmits X chromosome positions for sex-averaged and male maps
  7. 3y agommconvertCRAN release adds chromosome lengths and smoothed Cox maps
  8. 3y agommconvertRecomputed Cox genetic maps and combined-array support
  9. 4y agommconvertRepoints data sources from master to main branches

Frequently asked questions

What is the difference between discretefdr and mmconvert?

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

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. discretefdr and mmconvert 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 discretefdr?

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

What are the best alternatives to mmconvert?

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