Pinned Repositories
Convert-matrix-to-Positive-Definite
Convert a (co)variance Matrix to the nearest positive definite matrix
convert-plink-file-to-blupf90-format
if you are working with a genotype data in Plink format (binary) or txt format, you might want to use blupf90 for genomic prediction or ssGBLUP GWAS
Convert_Genotype_code_2_Plink_format
Converting genotype code (0, 1 and 2) to plink format using both R and shell script
Cross-validation-with-BLUPf90-programs
Five-fold cross-validation with BLUPf90 programs
DeepLearnings-Methods
Genomic Selection Methods: Deep Learnings vs. Ensemble and Parametric Methods
NGS-Analysis
Work Flow for NGS Analysis
Non_additive_simulation_R
This R-script is a part of simulation code used for our published paper in GSE
QMSim_genomic_evaluation
Genomic_evaluation with QMSim using external file
Random-Regression-Analysis
Generating Legendre Polynomials coefficients and computing the Breeding Values based on Test-day Milk data in dairy cattle
Single-and-Multi-trait-IFM-Simulation
Rostamabd's Repositories
Rostamabd/Non_additive_simulation_R
This R-script is a part of simulation code used for our published paper in GSE
Rostamabd/Single-and-Multi-trait-IFM-Simulation
Rostamabd/Convert-matrix-to-Positive-Definite
Convert a (co)variance Matrix to the nearest positive definite matrix
Rostamabd/NGS-Analysis
Work Flow for NGS Analysis
Rostamabd/QMSim_genomic_evaluation
Genomic_evaluation with QMSim using external file
Rostamabd/Random-Regression-Analysis
Generating Legendre Polynomials coefficients and computing the Breeding Values based on Test-day Milk data in dairy cattle
Rostamabd/convert-plink-file-to-blupf90-format
if you are working with a genotype data in Plink format (binary) or txt format, you might want to use blupf90 for genomic prediction or ssGBLUP GWAS
Rostamabd/Convert_Genotype_code_2_Plink_format
Converting genotype code (0, 1 and 2) to plink format using both R and shell script
Rostamabd/Cross-validation-with-BLUPf90-programs
Five-fold cross-validation with BLUPf90 programs
Rostamabd/DeepLearnings-Methods
Genomic Selection Methods: Deep Learnings vs. Ensemble and Parametric Methods
Rostamabd/Gene-Content-Heritabilty
Detecting low-quality SNPs, by estimating the proportion of variation of each SNP is explained by pedigree information. It is expected this estimate to be 1. but in case of genotyping errors or genotypes are wrongly assigned to a large proportion of individuals, this value will be lower than one and it can denote the low-quality of SNP.
Rostamabd/LD_decay
Linkage Disequilibrium decay over distances for multiple populations