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kde1d vs qtl2

A side-by-side editorial comparison of kde1d and qtl2 — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r-package

kde1d vs qtl2: at a glance

Featurekde1dqtl2
SectorAnalyticsAnalytics
Velocity score0.02.5
Sparks · 30d00
Top themesdensity-estimation, kernel-methods, zero-inflation, cpp-libraryqtl-mapping, statistical-genetics, bioinformatics, r-package
Last editorial update1h ago6h ago
WebsiteVisit →Visit →

What is kde1d?

A univariate density estimator that added zero-inflated data and reopened its C++ API to do it.

kde1d estimates univariate densities with local polynomial kernel methods, handling bounded, discrete and now zero-inflated variables through a single type argument, with the numerical work in a header-only C++ library usable outside R. Version 1.1.0 added the zero-inflated discrete-continuous mixture case and shipped a new C++ API as an explicit breaking change; 1.1.1 followed in June with auto-generated notes and no description.

Read the full kde1d trajectory →

What is qtl2?

The standard QTL mapping package in R opened its genome scan to user-supplied likelihood models.

qtl2 is the R toolkit for QTL mapping in experimental crosses, covering genotype probability calculation, genome scans with and without polygenic effects, permutation testing, SNP association, and the plotting that goes with them. The last year of work has pushed hard in two directions: tooling for high-throughput expression and protein QTL studies, and a generalisation of the scan engine itself so the log-likelihood being maximised can be supplied by the user. Note that the release history reached this feed out of order, so feed position is not a reliable guide to which release came first.

Read the full qtl2 trajectory →

kde1d vs qtl2: editorial side-by-side

K
kde1d
ANALYTICS
0.0

A univariate density estimator that added zero-inflated data and reopened its C++ API to do it.

◆ Current state

kde1d estimates univariate densities with local polynomial kernel methods, handling bounded, discrete and now zero-inflated variables through a single type argument, with the numerical work in a header-only C++ library usable outside R. Version 1.1.0 added the zero-inflated discrete-continuous mixture case and shipped a new C++ API as an explicit breaking change; 1.1.1 followed in June with auto-generated notes and no description.

◆ Where it's heading

The package has alternated between performance work and widening the class of data it accepts. The 1.0.0 release was the performance milestone — FFT-based estimation, a better integration algorithm for the p, q and r functions, deterministic jittering replacing randomness, and standalone C++ headers. The 1.1.0 release is the scope milestone, adding a third data type to the two it already handled. Releases come from the same maintainer as svines and cluster on shared dates, so changes in the underlying C++ surface across the vine and density stack tend to ship together.

◆ Prediction

With the C++ API deliberately reworked for standalone use at 1.1.0, further work most plausibly consolidates that interface rather than adding data types. What 1.1.1 actually changed is not readable from its body.

Q
qtl2
ANALYTICS
2.5

The standard QTL mapping package in R opened its genome scan to user-supplied likelihood models.

◆ Current state

qtl2 is the R toolkit for QTL mapping in experimental crosses, covering genotype probability calculation, genome scans with and without polygenic effects, permutation testing, SNP association, and the plotting that goes with them. The last year of work has pushed hard in two directions: tooling for high-throughput expression and protein QTL studies, and a generalisation of the scan engine itself so the log-likelihood being maximised can be supplied by the user. Note that the release history reached this feed out of order, so feed position is not a reliable guide to which release came first.

◆ Where it's heading

The eQTL and pQTL direction is the clearest thread — cis-trans plots, hotspot counting over a sliding window, multi-trait scan heat maps, and genome-wide genotype plots all arrived together, which is the toolkit an experiment with thousands of traits needs rather than one with a handful. Running underneath it is a steady generalisation of the core: a scan function that accepts an arbitrary likelihood, permutations that work with alternative scan functions, full variance-covariance output from single-position fits. Performance and parallelism get attention each cycle, including a more considerate default that leaves one core free. The rest is the ordinary maintenance of a long-lived package — renames to avoid tidyverse collisions, compiler warnings, and correctness fixes on specific cross types.

◆ Prediction

With scan1gen and permutation support for alternative scan functions in place, the natural next step is more model types built on that hook rather than more special-cased scan functions; the entries do not indicate which models are planned.

Alternatives to kde1d and qtl2

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 kde1d or qtl2.

See all kde1d alternatives → · See all qtl2 alternatives →

Recent activity from kde1d and qtl2

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

  1. 27d agoqtl2chr_lengths() extended to cross2 objects
  2. 1mo agoqtl2A genome scan that takes your own likelihood function
  3. 2mo agoqtl2Hotspot counting and cis-trans plots for eQTL studies
  4. 3mo agoqtl2Confidence interval plotting, plus a documentation correction
  5. 1y agokde1dkde1d 1.1.1
  6. 1y agoqtl2Finer-grained parallelism for kinship-based scans
  7. 1y agoqtl2CSV readers renamed to avoid the readr collision
  8. 1y agokde1dZero-inflated mixtures and a new standalone C++ API
  9. 4y agokde1dBit-wise Boolean operations removed
  10. 5y agokde1ddkde1d() invisible output fixed
  11. 5y agokde1dValgrind false positive silenced
  12. 6y agokde1dqrng dependency dropped; undefined behaviour fixed

Frequently asked questions

What is the difference between kde1d and qtl2?

Both compete on the same themes — r-package — within Analytics. qtl2 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 kde1d better than qtl2?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. qtl2 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 kde1d?

Top kde1d alternatives in Analytics are ranked by recent ship velocity. Browse the "kde1d alternatives" section above for the current picks, or visit /alternatives/kde1d for the full list with editorial commentary on each.

What are the best alternatives to qtl2?

Top qtl2 alternatives in Analytics are ranked by recent ship velocity. Browse the "qtl2 alternatives" section above for the current picks, or visit /alternatives/qtl2 for the full list with editorial commentary on each.