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assesslite vs qtl2

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

assesslite vs qtl2: at a glance

Featureassessliteqtl2
SectorAnalyticsAnalytics
Velocity score0.02.5
Sparks · 30d00
Top themescausal-inference, reproducibility, statistical-auditing, python-r-parityqtl-mapping, statistical-genetics, bioinformatics, r-package
Last editorial update1h ago48m ago
WebsiteVisit →Visit →

What is assesslite?

Four releases in fifteen hours take causal assumption-checking from resampling to identification

AssessLite attacks the structural assumptions behind a causal finding and returns three-way verdicts — stable, unstable, or not resolvable — feeding proceed, conditional or abstain decisions, with an auditable JSON record validated against a shared schema. It runs natively in R and Python against one spec, with the Python engine reproducing R's coxph(ties=breslow) exactly. The entire 0.1.0-through-0.4.0 arc landed inside a single day in July 2026.

Read the full assesslite 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 →

assesslite vs qtl2: editorial side-by-side

A
assesslite
ANALYTICS
0.0

Four releases in fifteen hours take causal assumption-checking from resampling to identification

◆ Current state

AssessLite attacks the structural assumptions behind a causal finding and returns three-way verdicts — stable, unstable, or not resolvable — feeding proceed, conditional or abstain decisions, with an auditable JSON record validated against a shared schema. It runs natively in R and Python against one spec, with the Python engine reproducing R's coxph(ties=breslow) exactly. The entire 0.1.0-through-0.4.0 arc landed inside a single day in July 2026.

◆ Where it's heading

The releases are cumulative, each restating the previous feature set and adding to it, so read them as one launch rather than four. The direction across that launch is clear: it started with resampling attacks (permutation, holdout, temporal split, subgroup), turned toward causal identification with declared DAGs and the backdoor criterion, then reached into genuinely dependent data with spatial and interference checks. The correctness work moves in step — the 0.3.0 Bonferroni adjustment fixed a holdout rule that was flagging roughly m times too often with m variants.

◆ Prediction

The project has repeatedly shipped what it previously listed as future work within days, so the next release most likely converts another declared gap rather than opening a new front.

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 assesslite 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 assesslite or qtl2.

See all assesslite alternatives → · See all qtl2 alternatives →

Recent activity from assesslite and qtl2

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

  1. 27d agoqtl2chr_lengths() extended to cross2 objects
  2. 1mo agoassessliteAssessLite 0.4.0
  3. 1mo agoassessliteAssessLite 0.3.0
  4. 1mo agoassessliteAssessLite 0.2.0
  5. 1mo agoassessliteAssessLite 0.1.0
  6. 1mo agoqtl2A genome scan that takes your own likelihood function
  7. 2mo agoqtl2Hotspot counting and cis-trans plots for eQTL studies
  8. 3mo agoqtl2Confidence interval plotting, plus a documentation correction
  9. 1y agoqtl2Finer-grained parallelism for kinship-based scans
  10. 1y agoqtl2CSV readers renamed to avoid the readr collision

Frequently asked questions

What is the difference between assesslite and qtl2?

They serve adjacent needs but don't currently overlap on shipped themes. 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 assesslite 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 assesslite?

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