Training Overview

Welcome to the UPLB-IRRI Internship/Training: Basic Bioinformatics Course under the UPLB and IRRI partnership. This training is designed to equip participants with the basic bioinformatics skills necessary for performing bioinformatics analysis.

Objective

The general objective of the training is to:

• Provide participants with the necessary bioinformatics skills for data manipulation, analysis, and the use of genomics-related bioinformatics software.
• Specifically, the course will focus on:
  • Training participants to use the Linux operating system. Performing Linux operations effectively.
  • Gaining hands-on experience with bioinformatics tools and techniques.

Format

This is a hybrid training setup.

---

Course Outline

Training 1: Sequence to Variants

Module 1: Introduction and Fundamentals

Objective: To introduce the Linux operating system and basic shell commands to equip students for command-line data analysis.

• Introduction to Linux
• Using WSL on Windows and installation guide
• Linux file system, hard and soft links, working directory
• Concept of shell, Linux processes, Environment variables, PATH variables, Shell expansion, Scripts
• Using Bash to manipulate common data formats (FASTA, SAM, VCF)

Module 2: NGS Data Analysis for Genotyping Purposes

Objective: To introduce the GATK workflow for variant calling and apply it to identify and characterize genetic variants in rice.

• Introduction to Second Generation Sequencing
• Variant Calling Pipeline
• Exploring VCF data, filtering, and basic statistics

---

Training 2: GWAS and Post-GWAS

Module 3: Basic GWAS Tutorial and Introduction to Internship Special Project

Objective: Introduction to GWAS methodology and acquiring practical skills in GWAS analysis of rice datasets.

• Population Structure and Rice Diversity
• Introduction to GWAS
• Interpreting GWAS outputs: Manhattan and QQ plots
• Hands-on: Population structure
• Hands-on: GWAS using TASSEL

Module 4: Post-GWAS using Rice SNP-Seek, Rice Galaxy, and RicePilaf.

Introduction to Special Project

Objective: Learn practical skills in interpreting GWAS output, integrating with other omics data, and identification of candidate genes.

• Significance threshold. Effective number of independent tests
• Linkage disequilibrium clumping
• Interrogating genomic regions with SNP-Seek and CropGalaxy
• Post-GWAS analysis using RicePilaf

Module 5: Special Project

Objective: To process, analyze, and interpret datasets using the skillsets learned from the training.