ArticleBioinformatics advances2025
Leveraging LASSO-based methodologies for enhanced SNP analysis in plant genomes.
Article in Bioinformatics advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
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Who cites it
1 citing paper in PubMed.
- From research to application: evaluation of literature-based and newly identified GWAS and GP-derived loci for anthracnose resistance in white lupin, across validation panels and environments.Molecular breeding : new strategies in plant improvement · 2026Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Summary: Genome-wide association studies (GWAS) have been widely used to reveal the associations between genetic variations and phenotypes in a population of individuals. However, they have been criticized for missing important genetic markers usually due to the fact that the data may not fit the statistical models well. In this study, we address the challenge of identifying significant single nucleotide polymorphisms (SNPs) in GWAS by harnessing the capabilities of two sophisticated regression models, BIGLASSO and AUTALASSO. They are both variants of the least absolute shrinkage and selection operator (LASSO). Our research contributes to the field of genomics through detailed comparative analysis of Availability and implementation: Key results from the paper are available at the https://github.com/DongdongHou006/LASSO-SNP. The program was implementated using Python and R, and was tested using the Digital Research Alliance of Canada.
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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 Socratic graph.