ArticlebioRxiv : the preprint server for biology2026
LT-FGRS: a unifying R-package for the estimation of family-based genetic liabilities at population-scale.
Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
Estimates of per-individual genetic liability from large-scale family data are routinely used in biomedical research to describe genetic etiology of traits and disorders, boost the power of gene-mapping studies, and improve risk predictions. Here we present LT-FGRS, an R package for handling population-scale pedigrees and implementing multiple state-of-the-field methods for estimating genetic liability from such data. Benchmarking in population-scale Nordic registry data demonstrates that LT-FGRS reproduces estimates from existing implementations at manageable computational cost. LT-FGRS unifies previous parallel implementations into a single framework, lowering barriers for methodological comparison and applied use.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.