nflreadr
The nflverse data loader, whose releases are dictated by the NFL calendar and CRAN's archive policy
Comparison · Analytics
mmconvert vs quanteda
A side-by-side editorial comparison of mmconvert and quanteda — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
mmconvert vs quanteda: at a glance
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.
What is quanteda?
Text analysis in R keeps optimising its token internals — and builds a path out to torch
quanteda is a mature framework for quantitative text analysis in R. Since the 4.0 rewrite around external-pointer tokens objects, releases have concentrated on the internals: recompilation control, memory reduction on concatenation, type-table consistency between tokens and dfm objects. The newest release adds tokens_recompile() for explicit ID reassignment, stops query functions from recompiling implicitly, and returns dense rather than sparse tensors from as.tensor() with arguments passed through to torch.
mmconvert vs quanteda: editorial side-by-side
mmconvert
0.0ANALYTICS
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.
quanteda
2.5ANALYTICS
Text analysis in R keeps optimising its token internals — and builds a path out to torch
◆ Current state
quanteda is a mature framework for quantitative text analysis in R. Since the 4.0 rewrite around external-pointer tokens objects, releases have concentrated on the internals: recompilation control, memory reduction on concatenation, type-table consistency between tokens and dfm objects. The newest release adds tokens_recompile() for explicit ID reassignment, stops query functions from recompiling implicitly, and returns dense rather than sparse tensors from as.tensor() with arguments passed through to torch.
◆ Where it's heading
Two threads run in parallel. The dominant one is performance and correctness housekeeping on the tokens_xptr representation introduced in 4.0 — each release closes another case where the external-pointer path diverged from the plain tokens path. The quieter thread points outward: as.matrix() returning a document-by-position integer matrix and as.tensor() handing off to torch::torch_tensor() make the tokenised corpus directly consumable by neural models rather than only by quanteda's own bag-of-words machinery.
◆ Prediction
The tensor and matrix export path is the least mature part of the surface and gained arguments in this release rather than settling, so expect further work there before the token internals change again.
Alternatives to mmconvert and quanteda
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 mmconvert or quanteda.
susier
Fine-mapping workhorse susieR spends its releases hunting null-effect trimming bugs
UCell
A rank-based gene signature scorer that has grown by adapting to whatever object format single-cell R uses next
detectseparation
A diagnostic package that generalized past its own name, then learned to say which kind of separation it found
brglm2
A bias-reduction package reaches 1.0 by adding an estimator built for high-dimensional logistic regression
bayestools
The JAGS toolkit under RoBMA, shipping the standardization machinery its downstream rewrite needed
See all mmconvert alternatives → · See all quanteda alternatives →
Recent activity from mmconvert and quanteda
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 12d agoquantedaExplicit token recompilation and a denser path out to torch
- 1mo agommconvertTest adjustment to clear a CRAN Note
- 1y agoquantedaCorpus chunking and cheaper token concatenation
- 1y agommconvertFixes a malformed warning message in mmconvert()
- 1y agoquantedaFaster concatenation and a dfm_lookup naming fix
- 2y agoquantedaMinor test and documentation fixes
- 2y agoquantedaPlatform-specific test and installation fixes
- 2y agoquantedaCRAN v4.0 ⚡
- 3y agommconvertOmits X chromosome positions for sex-averaged and male maps
- 3y agommconvertCRAN release adds chromosome lengths and smoothed Cox maps
- 3y agommconvertRecomputed Cox genetic maps and combined-array support
- 4y agommconvertRepoints data sources from master to main branches
Frequently asked questions
What is the difference between mmconvert and quanteda?
Both compete on the same themes — r-package — within Analytics. quanteda is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Is mmconvert better than quanteda?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. quanteda is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
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.
What are the best alternatives to quanteda?
Top quanteda alternatives in Analytics are ranked by recent ship velocity. Browse the "quanteda alternatives" section above for the current picks, or visit /alternatives/quanteda for the full list with editorial commentary on each.