A Hands-On Program for Genomic Data Analysis
Unlocking Insights: A Practical Journey in Genomic Data Analysis
Skills you will gain:
This one-month intensive program is designed to provide participants with a thorough introduction to genomic data analysis. Through interactive sessions, attendees will learn how to access genomic databases, retrieve relevant data, and utilize bioinformatics tools for analysis. Participants will engage in practical exercises to analyze real-world genomic datasets, enhancing their understanding of the data’s implications in biological research and medical applications.
The program emphasizes a hands-on approach, allowing participants to work with tools like NCBI and UCSC Genome Browser, making the learning experience both engaging and applicable. By the end of the day, attendees will have gained valuable insights into the methodologies used in genomic research, preparing them for further exploration in the field of bioinformatics.
Aim: This program aims to equip participants with practical skills in genomic data analysis through hands-on experience using popular bioinformatics tools. Participants will explore genomic data retrieval, analysis, and visualization, enabling them to understand the underlying biological significance of genomic sequences.
Program Objectives:
- To understand the basics of genomic data and its significance.
- To gain proficiency in using bioinformatics tools for data analysis.
- To analyze genomic datasets using practical techniques.
- To visualize and interpret genomic data effectively.
- To enhance problem-solving skills in genomic research scenarios.
What you will learn?
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Week 1: Introduction to Genomics and Data Types
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Basics of genome organization and sequencing technologies
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NGS platforms: Illumina, Oxford Nanopore, PacBio
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Types of genomic data: FASTQ, BAM, VCF, GFF
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Introduction to Linux and command-line interfaces for bioinformatics
Week 2: Sequence Data Quality Control and Alignment
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Quality assessment using FastQC and trimming tools (Trimmomatic, Cutadapt)
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Genome indexing and alignment using BWA/Bowtie2
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File conversions and manipulations using SAMtools
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Hands-on exercises with reference genome and raw data
Week 3: Variant Calling, Annotation, and Interpretation
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SNP and Indel calling with GATK, FreeBayes
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Functional annotation using ANNOVAR and SnpEff
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Integrating variant data with databases (ClinVar, dbSNP, gnomAD)
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Interpreting disease-associated mutations and population variation
Week 4: Transcriptomics and Advanced Analytical Workflows
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RNA-Seq data processing and differential gene expression (DESeq2, edgeR)
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Visualization tools: IGV, UCSC Genome Browser, heatmaps, PCA
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Functional enrichment: GO, KEGG, Reactome
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Introduction to machine learning in genomic data classification
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Intended For :
- Undergraduate degree in Biology, Bioinformatics, Computer Science, or related fields.
- Professionals in healthcare, research, or related industries.
- Individuals with a strong interest in genetics and data analysis.
Career Supporting Skills