Technical Tools & Software

Comprehensive expertise in statistical software, genetic analysis tools, and programming languages

Statistical SoftwareGenetic AnalysisProgramming

Technical Expertise Overview

Core Technical Areas
  • • Statistical Software (R, SAS, SPSS)
  • • Genetic Analysis Software
  • • Molecular Biology Techniques
  • • Data Analysis & Visualization
  • • Experimental Design
Advanced Applications
  • • Linux/Unix System Administration
  • • High-Performance Computing
  • • Cloud Computing Platforms
  • • Database Management
  • • Bioinformatics Pipelines

Statistical Software Expertise

R Programming Language

Advanced proficiency in R for statistical analysis, data visualization, and genetic analysis.

Statistical Analysis

  • • Linear and mixed-effects models (lme4, nlme)
  • • Generalized linear models (glm, glmmTMB)
  • • Survival analysis (survival, coxme)
  • • Time series analysis (forecast, tseries)
  • • Multivariate analysis (vegan, FactoMineR)

Genetic Analysis Packages

  • • Quantitative genetics (rrBLUP, BGLR)
  • • QTL mapping (qtl, R/qtl2)
  • • Population genetics (adegenet, hierfstat)
  • • Phylogenetics (ape, phangorn)
  • • Genomic selection (BGLR, rrBLUP)
SAS & SPSS

Enterprise-level statistical analysis for large-scale breeding programs and research.

SAS Applications

  • • PROC MIXED for mixed models
  • • PROC GLM for general linear models
  • • PROC GENMOD for generalized models
  • • PROC PHREG for survival analysis
  • • PROC IML for matrix operations

SPSS Applications

  • • Complex survey data analysis
  • • Multivariate analysis procedures
  • • Custom tables and reporting
  • • Syntax programming
  • • Integration with other systems

Genetic Analysis Software

BLUPF90 Family

Comprehensive suite for genetic evaluation and genomic prediction in livestock breeding.

Core Programs

  • • BLUPF90 for basic genetic evaluation
  • • AIREMLF90 for variance component estimation
  • • GIBBSF90 for Bayesian analysis
  • • GBLUPF90 for genomic prediction
  • • POSTGSF90 for post-analysis

Advanced Applications

  • • Single-step genomic evaluation
  • • Multi-trait analysis
  • • Random regression models
  • • Reaction norm models
  • • Custom likelihood functions
PLINK & Genomic Tools

Comprehensive toolkit for genome-wide association studies and genomic data management.

PLINK Applications

  • • Quality control and filtering
  • • Population structure analysis
  • • Association testing
  • • Haplotype analysis
  • • LD calculation and visualization

Other Genomic Tools

  • • GCTA for genetic relationship analysis
  • • EIGENSOFT for population stratification
  • • VCFtools for variant analysis
  • • BEDTools for genomic intervals
  • • SAMtools for sequence analysis

Programming & System Skills

Linux/Unix & Shell Scripting

Advanced Linux system administration and shell scripting for bioinformatics workflows.

System Administration

  • • User and permission management
  • • Process monitoring and control
  • • System performance optimization
  • • Backup and recovery procedures
  • • Security hardening

Shell Scripting

  • • Bash scripting for automation
  • • Pipeline development
  • • File system operations
  • • Text processing with awk/sed
  • • Job scheduling with cron
Python Programming

Python programming for data analysis, machine learning, and bioinformatics applications.

Data Science Libraries

  • • NumPy for numerical computing
  • • Pandas for data manipulation
  • • Matplotlib/Seaborn for visualization
  • • Scikit-learn for machine learning
  • • SciPy for scientific computing

Bioinformatics Tools

  • • Biopython for sequence analysis
  • • PyVCF for variant analysis
  • • DendroPy for phylogenetics
  • • NetworkX for network analysis
  • • TensorFlow/PyTorch for deep learning
Database & Big Data Technologies

Database management and big data technologies for handling large-scale genomic datasets.

Database Systems

  • • MySQL/MariaDB for relational data
  • • PostgreSQL for advanced analytics
  • • MongoDB for document storage
  • • SQLite for lightweight applications
  • • Redis for caching

Big Data Technologies

  • • Apache Hadoop ecosystem
  • • Apache Spark for distributed computing
  • • Docker for containerization
  • • Kubernetes for orchestration
  • • Cloud platforms (AWS, GCP, Azure)

Technical Collaboration

Partner in implementing advanced technical solutions for agricultural research