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mice vs valr

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

mice vs valr: at a glance

Featuremicevalr
SectorInfra & APIsInfra & APIs
Velocity score0.00.0
Sparks · 30d00
Top themesmissing-data, multiple-imputation, statistics, r-packagegenomics, interval-arithmetic, bioinformatics, bigwig
Last editorial update1h ago3h ago
WebsiteVisit →Visit →

What is mice?

mice can finally predict, not just estimate, from multiply imputed data.

mice is the reference implementation of multiple imputation by chained equations, and the default answer to missing data in R. The releases here follow a consistent shape: one or two substantive additions per version, most contributed by outside authors, plus fixes to methods that have been in the package for years. The current 3.19.0 adds predict_mi(), which pools predictions across imputations under Rubin's rules and can return prediction intervals.

Read the full mice trajectory →

What is valr?

valr's interval verbs now read genomic files in place instead of demanding a loaded tibble.

valr reimplements bedtools-style genome interval arithmetic as tidyverse verbs backed by C++. Its long project has been closing the behavioural gap with bedtools — the book-ended interval semantics finally match in 0.10.0, three releases after the deprecation began. The July release also ends the assumption that intervals must be in memory: bed_map(), bed_intersect(), bed_subtract(), bed_coverage() and bed_window() accept a bigWig or bigBed path or URL where an interval table used to go.

Read the full valr trajectory →

mice vs valr: editorial side-by-side

M
mice
INFRA · APIS
0.0

mice can finally predict, not just estimate, from multiply imputed data.

◆ Current state

mice is the reference implementation of multiple imputation by chained equations, and the default answer to missing data in R. The releases here follow a consistent shape: one or two substantive additions per version, most contributed by outside authors, plus fixes to methods that have been in the package for years. The current 3.19.0 adds predict_mi(), which pools predictions across imputations under Rubin's rules and can return prediction intervals.

◆ Where it's heading

Two things are happening. The imputation method catalogue keeps widening — lasso variants, multivariate PMM, categorical PMM via canonical correlation — while the pooling side is being extended past its original purpose, first to synthetic data, now to predictions on held-out sets. That second thread points at predictive modelling workflows rather than the inferential ones mice was built for. Meanwhile the maintainers keep finding consequential old bugs: the augment() ordered-factor defect in 3.18.0 had been silently degrading ordinal imputations for years.

◆ Prediction

predict_mi() is framed around evaluating predictive performance on test sets, and the ignore argument added in 3.12.0 already exists to hold out rows from the imputation model. Expect the next work to join those up into a fuller train/test story for imputed data, since the pieces are now in place but not yet connected.

V
valr
INFRA · APIS
0.0

valr's interval verbs now read genomic files in place instead of demanding a loaded tibble.

◆ Current state

valr reimplements bedtools-style genome interval arithmetic as tidyverse verbs backed by C++. Its long project has been closing the behavioural gap with bedtools — the book-ended interval semantics finally match in 0.10.0, three releases after the deprecation began. The July release also ends the assumption that intervals must be in memory: bed_map(), bed_intersect(), bed_subtract(), bed_coverage() and bed_window() accept a bigWig or bigBed path or URL where an interval table used to go.

◆ Where it's heading

Two arcs converge here. One is compatibility: min_overlap arrived with a deprecation warning in 0.9.0 and its default flipped from 0 to 1 in 0.10.0, so book-ended intervals are excluded by default as bedtools does, with the internal calculations in bed_closest() and friends deliberately left counting them. The other is the file-backed path, which grew out of the cpp11bigwig dependency adopted in 0.8.3 for read_bigwig() and re-exported in 0.9.0 — reading a file became querying one. Underneath, the C++ base keeps getting lighter: Rcpp swapped for cpp11, rlang cut to a single function, per-group memory copies removed from three verbs.

◆ Prediction

Only five verbs take a file argument today and bed_closest(), bed_glyph() and the statistical verbs do not, so extending the file-backed path across the rest of the API is the obvious follow-up. The deprecated tibble re-exports and the now-defunct n_fields argument suggest continued removal of the compatibility layer in the next minor release.

Alternatives to mice and valr

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 mice or valr.

See all mice alternatives → · See all valr alternatives →

Recent activity from mice and valr

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

  1. 1mo agovalrInterval verbs read bigWig and bigBed files directly
  2. 7mo agovalrbed_slop() and bed_flank() preserve input row order
  3. 8mo agomicemice 3.19.0
  4. 8mo agovalrmin_overlap introduced; C++ backend moves from Rcpp to cpp11
  5. 1y agovalrTest updated for ggplot2 3.6.0
  6. 1y agomicemice 3.18.0
  7. 1y agovalrread_bigwig() switches to cpp11bigwig; read_gtf() deprecated
  8. 1y agomicemice 3.17.0
  9. 1y agovalrCRAN Rd link NOTE and maintainer email change
  10. 3y agomicemice 3.16.0
  11. 3y agomicemice 3.15.0
  12. 4y agomicemice 3.14.0

Frequently asked questions

What is the difference between mice and valr?

They serve adjacent needs but don't currently overlap on shipped themes. mice and valr 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 mice better than valr?

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

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

What are the best alternatives to valr?

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