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Affymetrix Probe ID Mapper Pathway Viewer MotifSampler w/ WebLOGO Blast Multiple Sequence Alignment Phylogeny Chromosome Visualizer Protein BioViewer Heatmap and Hierarchical Clustering ScatterPlot SNPViz Targeted Sequence Selection Distance Matrix Mutant Finder Enrichment Analysis SoyCSN AccuTool Soybean Allele Catalog Tool Soybean Genomic Variations Explorer Soybean MADis Tool
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SoyHub
Welcome to Soy Hub
A hub for soybean-applied genomics predictions based on a curated panel of diverse soybean resequenced accessions (Soy1066).
Explore variation:
Allele Catalog- Find accessions with certain allele
- Find new alleles in known genes
GenVarX- Explore variation in promoters
- Search TFs
- Explore CNV
MADis- Mutative allele discovery
- Mutative allele position combinative calculations
Predict new causal mutations:
AccuTool- Use GWAS results for prediction
- Calculate Accuracy for your markers or candidate causative mutations (CM) based on Soy775 35.7M variant positions
SNPViz- Check genomic context of your variant positions in empowered haplotype viewer on various resequenced data sets
Reference Interassembly Gene Browser- Search between reference genotypes, genome assemblies, or annotation versions
References:
Allele Catalog
[1] Chan YO, Dietz N, Zeng S, Wang J, Flint-Garcia S, Salazar-Vidal MN, Škrabišová M, Bilyeu K, Joshi T: The Allele Catalog Tool: a web-based interactive tool for allele discovery and analysis. BMC Genomics 2023, 24(1):107.
GenVarX
[1] Chan YO, Biova J, Mahmood A, Dietz N, Bilyeu K, Škrabišová M, Joshi T: Genomic Variations Explorer (GenVarX): A Toolset for Annotating Promoter and CNV Regions Using Genotypic and Phenotypic Differences. Frontiers in Genetics 2023, In Press.
AccuTool
[1] Biová J, Dietz N, Chan YO, Joshi T, Bilyeu K, Škrabišová M: AccuCalc: A Python Package for Accuracy Calculation in GWAS. Genes 2023, 14(1):123.
[2] Škrabišová M, Dietz N, Zeng S, Chan YO, Wang J, Liu Y, Biová J, Joshi T, Bilyeu KD: A novel Synthetic phenotype association study approach reveals the landscape of association for genomic variants and phenotypes. Journal of Advanced Research 2022, 42:117-133.
MADis
[1] Biová J, Kaňovská I, Chan YO, Immadi MS, Joshi T, Bilyeu K, Škrabišová M. Natural and artificial selection of multiple alleles revealed through genomic analyses. Front Genet. 2024 Jan 8;14:1320652. doi: 10.3389/fgene.2023.1320652. PMID: 38259621; PMCID: PMC10801239.
SNPViz
[1] Zeng S, Škrabišová M, Lyu Z, Chan YO, Dietz N, Bilyeu K, Joshi T: Application of SNPViz v2.0 using next-generation sequencing data sets in the discovery of potential causative mutations in candidate genes associated with phenotypes. International Journal of Data Mining and Bioinformatics 2021, 25(1-2):65-85.
[2] Zeng S, Škrabišová M, Lyu Z, Chan YO, Bilyeu K, Joshi T: SNPViz v2.0: A web-based tool for enhanced haplotype analysis using large scale resequencing datasets and discovery of phenotypes causative gene using allelic variations. In: 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM): 16-19 Dec. 2020; 2020: 1408-1415.
[3] Langewisch T, Zhang H, Vincent R, Joshi T, Xu D, Bilyeu K: Major soybean maturity gene haplotypes revealed by SNPViz analysis of 72 sequenced soybean genomes. PLoS One 2014, 9(4):e94150.
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Predict new causal mutations by GWAS to Genes approach:
Synthetic phenotype to causal mutation strategy (SP2CM)
For more details, please see:
Škrabišová M, Dietz N, Zeng S, Chan YO, Wang J, Liu Y, Biová J, Joshi T, Bilyeu KD (2022) A novel Synthetic phenotype association study approach reveals the landscape of association for genomic variants and phenotypes. Journal of Applied Research, 42:117-133. 10.1016/j.jare.2022.04.004