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healthyR.data vs qtl2

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

Shared themes:r-package

healthyR.data vs qtl2: at a glance

FeaturehealthyR.dataqtl2
SectorAnalyticsAnalytics
Velocity score0.02.5
Sparks · 30d00
Top themesr-package, healthcare-data, cms, api-clientqtl-mapping, statistical-genetics, bioinformatics, r-package
Last editorial update1h ago7h ago
WebsiteVisit →Visit →

What is healthyR.data?

From a bundled hospital dataset to a live CMS API client.

healthyR.data supplies the data layer for the healthyverse packages. It began by shipping hospital data inside the package and now fetches from CMS and provider endpoints at call time through get_cms_meta_data(), fetch_cms_data(), and their provider counterparts. The most recent release is a single httr2 compatibility fix.

Read the full healthyR.data 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 →

healthyR.data vs qtl2: editorial side-by-side

H
healthyR.data
ANALYTICS
0.0

From a bundled hospital dataset to a live CMS API client.

◆ Current state

healthyR.data supplies the data layer for the healthyverse packages. It began by shipping hospital data inside the package and now fetches from CMS and provider endpoints at call time through get_cms_meta_data(), fetch_cms_data(), and their provider counterparts. The most recent release is a single httr2 compatibility fix.

◆ Where it's heading

The 2023 release added roughly twenty current_*_data() accessors, one per CMS measure file - a wide but static surface. The 2024 releases replaced that approach with metadata lookup plus generic fetchers, then taught the fetchers to handle CSV, Excel, and ZIP payloads rather than API responses alone. The package's weight has moved from what it ships to what it can retrieve.

◆ Prediction

With the fetch layer generalised, the next visible work is more likely record-limit and error handling around httr2 than further per-measure accessors.

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 healthyR.data 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 healthyR.data or qtl2.

See all healthyR.data alternatives → · See all qtl2 alternatives →

Recent activity from healthyR.data 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 agoqtl2Finer-grained parallelism for kinship-based scans
  6. 1y agoqtl2CSV readers renamed to avoid the readr collision
  7. 1y agohealthyR.datahttr2 compatibility fix
  8. 2y agohealthyR.dataFetchers handle CSV, Excel, and ZIP, with a record limit
  9. 2y agohealthyR.dataMetadata lookup and generic CMS fetchers replace bundled data
  10. 3y agohealthyR.dataTwenty CMS measure accessors added
  11. 3y agohealthyR.datacli, crayon, and rstudioapi dependencies dropped
  12. 5y agohealthyR.dataxz compression added to meet CRAN size policy

Frequently asked questions

What is the difference between healthyR.data 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 healthyR.data 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 healthyR.data?

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