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glyfun vs ribd

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

glyfun vs ribd: at a glance

Featureglyfunribd
SectorAnalyticsAnalytics
Velocity score0.02.5
Sparks · 30d00
Top themesglycomics, enrichment analysis, bioconductor, r packagesstatistical-genetics, pedigree-analysis, relatedness-coefficients, r-packages
Last editorial update36m ago1h ago
WebsiteVisit →Visit →

What is glyfun?

glyfun is three releases old and has spent all of them chasing glyexp's container change.

glyfun is the newest glycoverse package, carved out to hold the enrichment analysis functions that glystats deprecated. Its entire visible history is the 0.1.x series, and all three releases are container plumbing: detected_universe() learning to accept GlycoproteomicSE, then the vignette and documentation following. There is no independent feature work in the record yet.

Read the full glyfun trajectory →

What is ribd?

The pedsuite's coefficient engine: broadening what it computes, then making the plots publishable.

ribd computes relatedness coefficients from pedigrees, covering kinship, inbreeding, kappa, condensed and detailed identity coefficients, and two-locus versions of several of these, in autosomal and X-chromosomal form. The IBD triangle is now drawable in base graphics, ggplot2 or plotly, with an optional inset pedigree, and custom relationships can be placed on it. The most recent release is dominated by correctness work, fixing pair ordering and row alignment in coefficient tables and edge cases for pedigree lists, unrelated individuals and self-pairs.

Read the full ribd trajectory →

glyfun vs ribd: editorial side-by-side

G
glyfun
ANALYTICS
0.0

glyfun is three releases old and has spent all of them chasing glyexp's container change.

◆ Current state

glyfun is the newest glycoverse package, carved out to hold the enrichment analysis functions that glystats deprecated. Its entire visible history is the 0.1.x series, and all three releases are container plumbing: detected_universe() learning to accept GlycoproteomicSE, then the vignette and documentation following. There is no independent feature work in the record yet.

◆ Where it's heading

This is a package being born into a migration rather than one navigating it. Because glystats removed its gly_enrich_*() functions outright and glysmith already routes enrichment through glyfun, the functional surface is inherited rather than designed here. The near-term arc is catching up to the rest of the stack; the interesting question is what glyfun adds once it is no longer just the relocation target.

◆ Prediction

Expect the first release with genuinely new enrichment capability rather than migration plumbing, most likely broadening the gene-set sources glystats never covered.

R
ribd
ANALYTICS
2.5

The pedsuite's coefficient engine: broadening what it computes, then making the plots publishable.

◆ Current state

ribd computes relatedness coefficients from pedigrees, covering kinship, inbreeding, kappa, condensed and detailed identity coefficients, and two-locus versions of several of these, in autosomal and X-chromosomal form. The IBD triangle is now drawable in base graphics, ggplot2 or plotly, with an optional inset pedigree, and custom relationships can be placed on it. The most recent release is dominated by correctness work, fixing pair ordering and row alignment in coefficient tables and edge cases for pedigree lists, unrelated individuals and self-pairs.

◆ Where it's heading

The arc runs from generality to presentation to precision. Early releases replaced narrow functions with general ones, most visibly when gKinship() absorbed generalisedKinship() and identityCoefs() superseded the separate autosomal and X-chromosomal identity functions in favour of an Xchrom argument. The middle stretch turned the IBD triangle into a proper plotting surface across three graphics systems. The current phase reads as consolidation, with the newest release listing six bug fixes against four features, several of them alignment errors in output tables, which is where a coefficient library most needs to be exactly right.

◆ Prediction

The two new internal functions in the latest release, inbreedingContributions() and ancestralKinship(), are the kind of thing that surfaces publicly a release or two later, so expect them to become exported decomposition tools. The correctness push through pedigree lists and edge cases suggests the near-term focus stays on hardening rather than new coefficient families.

Alternatives to glyfun and ribd

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 glyfun or ribd.

See all glyfun alternatives → · See all ribd alternatives →

Recent activity from glyfun and ribd

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

  1. 12d agoribdCustom relationships on the IBD triangle; six alignment and edge-case fixes
  2. 1mo agoglyfunDocs move to GlycoproteomicSE inputs
  3. 1mo agoglyfunVignette runs against both container types
  4. 1mo agoglyfundetected_universe() accepts GlycoproteomicSE objects
  5. 1y agoribdkappaIBD() can skip across-component pairs on large pedigrees
  6. 2y agoribdIBD triangle plots gain ggplot2 and plotly backends, plus inset pedigrees
  7. 3y agoribdTriangle line clipping, automatic plot margins, citation info
  8. 3y agoribdTwo-locus functions overhauled; twoLocusInbreeding and ELR added
  9. 4y agoribdIdentity coefficients unified behind identityCoefs() and an Xchrom argument

Frequently asked questions

What is the difference between glyfun and ribd?

They serve adjacent needs but don't currently overlap on shipped themes. ribd 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 glyfun better than ribd?

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

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

What are the best alternatives to ribd?

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