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fillpattern vs qtl2

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

Shared themes:r-package

fillpattern vs qtl2: at a glance

Featurefillpatternqtl2
SectorAnalyticsAnalytics
Velocity score0.02.5
Sparks · 30d00
Top themesggplot2, data-visualization, accessibility, graphicsqtl-mapping, statistical-genetics, bioinformatics, r-package
Last editorial update1h ago3h ago
WebsiteVisit →Visit →

What is fillpattern?

Pattern fills for ggplot2, hardened against the ways users write sizes

fillpattern provides pattern fills — stripes, bricks, dots — for ggplot2 and base R graphics, aimed at figures that must stay legible in greyscale or to colour-blind readers. The 1.0.3 release is mostly defensive: size modifier strings ending in a colon no longer swap width for height, modify_size() reports invalid units instead of crashing and understands in, inches and cm, and a background colour bug in scale_fill_pattern() is fixed. The minimum R version rises to 4.2.0 for recent graphics engine features.

Read the full fillpattern 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 →

fillpattern vs qtl2: editorial side-by-side

F
fillpattern
ANALYTICS
0.0

Pattern fills for ggplot2, hardened against the ways users write sizes

◆ Current state

fillpattern provides pattern fills — stripes, bricks, dots — for ggplot2 and base R graphics, aimed at figures that must stay legible in greyscale or to colour-blind readers. The 1.0.3 release is mostly defensive: size modifier strings ending in a colon no longer swap width for height, modify_size() reports invalid units instead of crashing and understands in, inches and cm, and a background colour bug in scale_fill_pattern() is fixed. The minimum R version rises to 4.2.0 for recent graphics engine features.

◆ Where it's heading

Development is slow and entirely reactive to how the string-based size interface fails. The pattern across releases is the same: a user hits an edge — very small fill areas in 1.0.2, malformed unit strings in 1.0.3 — and the fix is either a graceful fallback or a clearer error. Leaning on R's newer graphics engine rather than reimplementing pattern rendering keeps the package small at the cost of raising its version floor.

◆ Prediction

Expect further releases to stay in the same register: parsing and validation fixes for the size and unit interface, with the pattern set itself unlikely to change.

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 fillpattern 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 fillpattern or qtl2.

See all fillpattern alternatives → · See all qtl2 alternatives →

Recent activity from fillpattern 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. 6mo agofillpatternSize string parsing fixed; invalid units now report instead of crash
  6. 1y agoqtl2Finer-grained parallelism for kinship-based scans
  7. 1y agoqtl2CSV readers renamed to avoid the readr collision
  8. 2y agofillpatternSmall fill areas no longer crash; min_size falls back to solid
  9. 2y agofillpatternfillpattern 1.0.1

Frequently asked questions

What is the difference between fillpattern 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 fillpattern 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 fillpattern?

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