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e2tree vs mmconvert

A side-by-side editorial comparison of e2tree and mmconvert — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r-package

e2tree vs mmconvert: at a glance

Featuree2treemmconvert
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesexplainable-ai, ensemble-methods, decision-trees, r-packager-package, genetics, genome-build, reference-data
Last editorial update1h ago39m ago
WebsiteVisit →Visit →

What is e2tree?

The explainable-ensemble-tree package now measures whether its own explanations are faithful.

e2tree builds a single interpretable tree that approximates a fitted ensemble, working from the proximity structure the ensemble induces between observations. The 1.0.0 release added the piece that had been missing: a Goodness of Interpretability index quantifying how well the approximating tree reconstructs the ensemble's own proximity matrix, with a permutation test for significance. Interactive visualisation and a C++ backend with OpenMP parallelism arrived alongside, and support now spans ranger and CatBoost as well as the original targets.

Read the full e2tree 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 →

e2tree vs mmconvert: editorial side-by-side

E
e2tree
ANALYTICS
0.0

The explainable-ensemble-tree package now measures whether its own explanations are faithful.

◆ Current state

e2tree builds a single interpretable tree that approximates a fitted ensemble, working from the proximity structure the ensemble induces between observations. The 1.0.0 release added the piece that had been missing: a Goodness of Interpretability index quantifying how well the approximating tree reconstructs the ensemble's own proximity matrix, with a permutation test for significance. Interactive visualisation and a C++ backend with OpenMP parallelism arrived alongside, and support now spans ranger and CatBoost as well as the original targets.

◆ Where it's heading

Development has moved from producing an explanation to defending it. The GoI index and its permutation test change the package's claim from here is a tree that resembles your ensemble to here is how closely it resembles it and whether that could have happened by chance — the question a reviewer asks of any surrogate model. Around that, the work is engineering: the proximity matrix construction moved from R-level parallel loops into C++ with thread-level parallelism, and recent releases have been absorbing the awkwardness of supporting multiple ensemble backends, where a multi-class CatBoost objective returns a score matrix where a vector was expected. Interactive visNetwork output and standalone HTML export point at explanations meant to be shared rather than only inspected.

◆ Prediction

Given how much recent effort has gone into per-backend adapters, expect further work on ensemble compatibility; the entries do not indicate whether the interpretability index is heading toward comparing surrogate trees against each other.

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 e2tree 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 e2tree or mmconvert.

See all e2tree alternatives → · See all mmconvert alternatives →

Recent activity from e2tree and mmconvert

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

  1. 1mo agommconvertTest adjustment to clear a CRAN Note
  2. 3mo agoe2treeCatBoost multi-class and loss-function handling repaired
  3. 4mo agoe2treeA significance-tested measure of explanation fidelity
  4. 1y agoe2treeranger models supported
  5. 1y agommconvertFixes a malformed warning message in mmconvert()
  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 e2tree and mmconvert?

Both compete on the same themes — r-package — within Analytics. e2tree 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 e2tree better than mmconvert?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. e2tree 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 e2tree?

Top e2tree alternatives in Analytics are ranked by recent ship velocity. Browse the "e2tree alternatives" section above for the current picks, or visit /alternatives/e2tree 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.