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qtl2 vs reliaplotr

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

Shared themes:r-package

qtl2 vs reliaplotr: at a glance

Featureqtl2reliaplotr
SectorAnalyticsAnalytics
Velocity score2.50.0
Sparks · 30d00
Top themesqtl-mapping, statistical-genetics, bioinformatics, r-packagereliability-engineering, r-package, plotly, mcp
Last editorial update1h ago1h ago
WebsiteVisit →Visit →

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 →

What is reliaplotr?

The Weibull plotting package renamed itself, then handed its charts to AI assistants.

ReliaPlotR draws interactive reliability plots with plotly — probability plots, contour plots, Duane and reliability growth charts, accelerated life testing plots by stress level, mean cumulative function curves for repairable systems, and exposure plots. It was WeibullR.plotly until late 2025, and the rename tracked a real widening of scope rather than just a label change. The current release adds tidy extractors that turn fitted model objects into data frames, and an MCP server exposing five of its fit and plot functions as tools.

Read the full reliaplotr trajectory →

qtl2 vs reliaplotr: editorial side-by-side

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.

R
reliaplotr
ANALYTICS
0.0

The Weibull plotting package renamed itself, then handed its charts to AI assistants.

◆ Current state

ReliaPlotR draws interactive reliability plots with plotly — probability plots, contour plots, Duane and reliability growth charts, accelerated life testing plots by stress level, mean cumulative function curves for repairable systems, and exposure plots. It was WeibullR.plotly until late 2025, and the rename tracked a real widening of scope rather than just a label change. The current release adds tidy extractors that turn fitted model objects into data frames, and an MCP server exposing five of its fit and plot functions as tools.

◆ Where it's heading

The package has been following its analysis siblings function for function: as accelerated life testing and repairable systems modelling landed in the wider suite, the matching plot types appeared here, and when the growth-analysis package shipped an MCP server, this one followed two weeks later. The tidy extractors point the same way — a plotting package that can also return parameter estimates, goodness-of-fit metrics, and confidence bounds as tidy frames is one designed to be consumed programmatically, by a pipeline or an assistant, not only read on screen. Overlaying multiple model fits on a single plot has been a recurring request answered across several releases.

◆ Prediction

Expect the tidy extractor and MCP tool surfaces to keep expanding together, since each new plot type in the suite now implies both a chart and a machine-readable version of what it shows.

Alternatives to qtl2 and reliaplotr

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 qtl2 or reliaplotr.

See all qtl2 alternatives → · See all reliaplotr alternatives →

Recent activity from qtl2 and reliaplotr

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. 2mo agoreliaplotrTidy model extractors plus five plotting tools over MCP
  5. 2mo agoreliaplotrNHPP plots switch to the mean cumulative function
  6. 3mo agoqtl2Confidence interval plotting, plus a documentation correction
  7. 4mo agoreliaplotrAccelerated life testing and repairable systems plots added
  8. 8mo agoreliaplotrDuane plots gain confidence bounds
  9. 9mo agoreliaplotrReliaPlotR v0.4.1
  10. 10mo agoreliaplotrRenamed from WeibullR.plotly to ReliaPlotR
  11. 1y agoqtl2Finer-grained parallelism for kinship-based scans
  12. 1y agoqtl2CSV readers renamed to avoid the readr collision

Frequently asked questions

What is the difference between qtl2 and reliaplotr?

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 qtl2 better than reliaplotr?

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 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.

What are the best alternatives to reliaplotr?

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