ArticleBioinformatics advances2023
HTRX: an R package for learning non-contiguous haplotypes associated with a phenotype.
Article in Bioinformatics advances, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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
3 citing papers in PubMed.
- Transformers for single-cell RNA sequencing: a survey.Briefings in bioinformatics · 2026Review
- Integrating Meta-QTL Analysis and Genome-Wide Association Mapping in Ethiopian Sesame (Plants (Basel, Switzerland) · 2026Article
- Elevated genetic risk for multiple sclerosis emerged in steppe pastoralist populations.Nature · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Summary: Haplotype Trend Regression with eXtra flexibility (HTRX) is an R package to learn sets of interacting features that explain variance in a phenotype. Genome-wide association studies (GWAS) have identified thousands of single nucleotide polymorphisms (SNPs) associated with complex traits and diseases, but finding the true causal signal from a high linkage disequilibrium block is challenging. We focus on the simpler task of quantifying the total variance explainable not just with main effects but also interactions and tagging, using haplotype-based associations. HTRX identifies haplotypes composed of non-contiguous SNPs associated with a phenotype and can naturally be performed on regions with a GWAS hit before or after fine-mapping. To reduce the space and computational complexity when investigating many features, we constrain the search by growing good feature sets using 'Cumulative HTRX', and limit the maximum complexity of a feature set. As the computational time scales linearly with the number of SNPs, HTRX has the potential to be applied to large chromosome regions. Availability and implementation: HTRX is implemented in R and is available under GPL-3 licence from CRAN (https://cran.r-project.org/web/packages/HTRX/readme/README.html). The development version is maintained on GitHub (https://github.com/YaolingYang/HTRX). Contact: yaoling.yang@bristol.ac.uk. Supplementary information: Supplementary data are available at
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.