gps2gtfs
gps2gtfs spent a release making its docs stop describing functions it does not have.
A side-by-side editorial comparison of glydet and ribd — release velocity, themes, recent moves, and the top alternatives to consider.
glydet is rebuilding its glycan trait vocabulary on top of someone else's container.
glydet derives glycan-derived traits from glycomics and glycoproteomics data. The 0.12.x line spent its releases absorbing glyexp's container migration: derive_traits(), quantify_motifs(), and add_meta_properties() now accept GlycomicSE and GlycoproteomicSE natively, with the legacy experiment() path kept only for backward-compatible return types. The substantive feature work sits one release back in 0.11.0, which added sialic acid linkage traits and three published trait sets.
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.
glydet derives glycan-derived traits from glycomics and glycoproteomics data. The 0.12.x line spent its releases absorbing glyexp's container migration: derive_traits(), quantify_motifs(), and add_meta_properties() now accept GlycomicSE and GlycoproteomicSE natively, with the legacy experiment() path kept only for backward-compatible return types. The substantive feature work sits one release back in 0.11.0, which added sialic acid linkage traits and three published trait sets.
Two threads run in parallel here. One is infrastructure: track glyexp's Stage II migration, drop the underscore matrix interfaces, and converge on a single trait column in var_info. The other is content: keep adding named trait sets from the literature (Clerc 2018, Li 2025, Fu 2026) so users cite a set rather than hand-roll definitions. The LLM-backed explain_trait() and make_trait() helpers are becoming provider-agnostic rather than deeper.
The trait catalogue is the growth area, so expect more published trait sets added as named functions, and the deprecated basic_traits() and all_traits() aliases to be removed once the container migration settles.
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.
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.
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.
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 glydet or ribd.
gps2gtfs spent a release making its docs stop describing functions it does not have.
ducksemantics puts an ontology graph and ColBERT retrieval inside DuckDB, callable from R.
dvir keeps making disaster victim identification a single call instead of a workflow.
pedbuildr reconstructs pedigrees from DNA, and it just got much faster at the search.
forrel is getting faster at the simulations forensic kinship work actually spends its time on.
pedFamilias exists to read one legacy file format, and it has that job nearly finished.
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
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.
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.
Top glydet alternatives in Analytics are ranked by recent ship velocity. Browse the "glydet alternatives" section above for the current picks, or visit /alternatives/glydet for the full list with editorial commentary on each.
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.