Supplementary Material for "Scalable medium-density genotyping platforms for cultivar identification, pedigree authentication, marker-assisted and genomic selection, and other applications in strawberry"

Supplemental Data Files for the manuscript "Scalable medium-density genotyping platforms for cultivar identification, pedigree authentication, marker-assisted and genomic selection, and other applications in strawberry". Briefly, this manuscript details the development of a new genotyping platform for strawberry and demonstrates its use in various applications various to strawberry research and breeding programs. 

Date files show results from analyses (Files 1, 2, 3, 4) or contain enabling R scripts (Files 5 and 6). Excel (.xlsx) files contain a worksheet labelled "Legend" which further describes all other worksheets in the supplement. R script (.R) files are annotated throughout and are not technology- or species-specific, only assuming the input of an allele-dosage-formatted genotype matrix (0, 0.5, 1; -1, 0, 1; or 0, 1, 2).

• Supplemental Data File 1: An Excel (.xlsx) file containing the results for identity-based analyses (purity testing and pedigree authentication).
• Supplemental Data File 2: An Excel (.xlsx) file containing the results for population structure analyses, e.g. GRM, PCA, k-means, STRUCTURE.
• Supplemental Data File 3: An Excel (.xlsx) file containing the results for genome-wide association analyses.
• Supplemental Data File 4: An Excel (.xlsx) file containing the results for breeding methodology analyses, e.g. genomic selection and prediction of marker-assisted selection targets via imputation.
• Supplemental Data File 5: A .zip file containing all R code utilized for the analyses in this this paper. All enabling inputs (including AgriSeq 1.5K, AgriSeq 4.5K, and FanaSNP 50K genotypic matrices) are provided.
• Supplemental Data File 6: A .zip file containing a much simplified R script detailing core analyses performed in this paper. Introductory and computationally inexpensive example datasets are provided.

Please refer to main publication, the "Legend" worksheets in .xlsx files, or the comments in .R scripts for additional details.