Post-imputation GBS dataset used specifically for GS cross-validation in Spindel et al., 2015. Dataset contains all markers with call rates >= .9 and lines that were included in the GS analysis (i.e., sub-population outliers are removed from this dataset). The data are formatted for use with the R rrBLUP package
Missing values are common in medical datasets and may be amenable to data imputation when modelling ...
Multiple imputation (MI) has become popular for analyses with missing data in medical research. The ...
Wheat GBS dataset with 25 % missing information. Genotypes are presented as rows and SNPs as columns...
Post-imputation GBS data for the IRRI breeding population used in Spindel et al., 2015 and Begum and...
<p>Box-plot derived from the imputation analysis of the largest GWAS <sup>(2)</sup>.</p
# GWAS summary statistics imputation, integration with PrediXcan MASHR-M The file `sample_data.t...
Compressed archive contains R script for identifying clusters in outlier SNP regions. Outlier SNP da...
textabstractBackground: Over the last few years, genome-wide association (GWA) studies became a tool...
D1-D3 were used for outlier detection; D4 was used for population genetic analyses; ten sub-datasets...
Genome-wide association studies are usually accompanied by imputation techniques to complement genom...
Genome-wide association studies are usually accompanied by imputation techniques to complement genom...
© 2015 Khankhanian, Din, Caillier, Gourraud and Baranzini.Imputation is a commonly used technique th...
Genotype imputation has become an essential tool in the analysis of genome-wide association scans. T...
SNP calls generated from high quality whole genome resequencing of 56 inbreds (Brohammer et al., 201...
<p>* Includes both genotypes originally called by GBS and following imputation</p><p>** 301soybean l...
Missing values are common in medical datasets and may be amenable to data imputation when modelling ...
Multiple imputation (MI) has become popular for analyses with missing data in medical research. The ...
Wheat GBS dataset with 25 % missing information. Genotypes are presented as rows and SNPs as columns...
Post-imputation GBS data for the IRRI breeding population used in Spindel et al., 2015 and Begum and...
<p>Box-plot derived from the imputation analysis of the largest GWAS <sup>(2)</sup>.</p
# GWAS summary statistics imputation, integration with PrediXcan MASHR-M The file `sample_data.t...
Compressed archive contains R script for identifying clusters in outlier SNP regions. Outlier SNP da...
textabstractBackground: Over the last few years, genome-wide association (GWA) studies became a tool...
D1-D3 were used for outlier detection; D4 was used for population genetic analyses; ten sub-datasets...
Genome-wide association studies are usually accompanied by imputation techniques to complement genom...
Genome-wide association studies are usually accompanied by imputation techniques to complement genom...
© 2015 Khankhanian, Din, Caillier, Gourraud and Baranzini.Imputation is a commonly used technique th...
Genotype imputation has become an essential tool in the analysis of genome-wide association scans. T...
SNP calls generated from high quality whole genome resequencing of 56 inbreds (Brohammer et al., 201...
<p>* Includes both genotypes originally called by GBS and following imputation</p><p>** 301soybean l...
Missing values are common in medical datasets and may be amenable to data imputation when modelling ...
Multiple imputation (MI) has become popular for analyses with missing data in medical research. The ...
Wheat GBS dataset with 25 % missing information. Genotypes are presented as rows and SNPs as columns...