New Year Offer End Date: 30th April 2024

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Program

Next-Generation Sequencing Data Analysis Program

Next-Generation Sequencing (NGS), Genomics, Bioinformatics, Data analysis, Quality control, Transcriptome analysis, Epigenetic analysis, Metagenomics, Molecular biology, Genetics,

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MODE
Mode(Online) TYPE
Self Paced LEVEL
Moderate Program Length
4.5 hours

Skills you will gain:

Bioinformatics Sequencing Alignment Transcriptomics

About Program:

The Next-Generation Sequencing Data Analysis Program is designed to offer participants a comprehensive understanding of the principles and techniques involved in analyzing data generated through next-generation sequencing (NGS) technologies. Through a combination of theoretical instruction and hands-on practical exercises, participants delve into various aspects of NGS data analysis, including read mapping, variant calling, transcriptome profiling, epigenetic analysis, and metagenomics. The program covers essential bioinformatics tools, algorithms, and pipelines commonly used in NGS data analysis, equipping participants with the skills needed to process, analyze, and interpret large-scale genomic datasets accurately. With a focus on real-world applications and research-driven projects, the program aims to empower participants to leverage NGS data to address complex biological questions and make significant contributions to fields such as genetics, medicine, agriculture, and environmental science.

Aim:

The aim of the “Next-Generation Sequencing Data Analysis Program” is to equip participants with the knowledge, skills, and tools necessary to effectively analyze and interpret data generated through next-generation sequencing (NGS) technologies. The program seeks to provide a comprehensive understanding of the principles, methods, and algorithms used in NGS data analysis, enabling participants to process, analyze, and interpret large-scale genomic datasets accurately. By covering topics such as read alignment, variant calling, transcriptome analysis, epigenetic analysis, and metagenomics, the program aims to empower participants to extract meaningful insights from NGS data and apply these insights to advance research in fields such as genomics, personalized medicine, evolutionary biology, and environmental science.

Program Objectives:

To provide participants with a solid understanding of the principles and methods used in NGS data analysis, including quality control, read alignment, variant calling, and annotation.
To equip participants with advanced knowledge and skills in NGS data analysis, including transcriptome analysis, epigenetic analysis, metagenomics, and de novo assembly.
To enable participants to apply these techniques to solve complex research questions and make meaningful scientific discoveries in the field of genomics.
To provide participants with hands-on experience in working with real-world datasets and using popular bioinformatics tools and pipelines for NGS data analysis.
To foster collaboration and networking among participants and instructors, providing valuable insights and feedback

What you will learn?

Day 1-

Introduction to NGS Technology
Overview of NGS data formats
Accessing NGS data using SRA tool kit
Quality control (FastQC) of reads

Day 2-

Processing of raw reads, adapter clipping, quality trimming
Read mapping (BWA, BWA-MEM, Bowtie2) to reference sequence
Mapping output (SAM/BAM format)
Visualization and evaluation of mapping quality
Variant Call File Format (VCF)

Day 3-

Bacterial whole genome assembly using SPADES
Assessment of genome assembly using BUSCO, QUAST
Genome Annotation
Functional annotation using EGG-NOG mapper

Fee Plan

INR 1999 /- OR USD 50

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Intended For :

Educational Background: Participants may be required to have a background in fields such as bioinformatics, computational biology, genetics, molecular biology, biotechnology, or a related discipline at the undergraduate or graduate level.
Basic Knowledge of Molecular Biology: Some programs may expect participants to have a fundamental understanding of molecular biology concepts, such as DNA sequencing technologies, gene expression, genetic variation, and biological databases.
Programming Skills: Proficiency in programming languages commonly used in bioinformatics, such as Python, R, or Perl, may be beneficial for effective participation in the program. However, introductory programming training may also be provided as part of the program.
Prior Experience: While not always mandatory, some programs may prefer participants with prior experience in bioinformatics, computational biology, or NGS data analysis through coursework, research projects, internships, or professional experience.
Interest and Motivation: Individuals with a strong interest in genomics, data analysis, and bioinformatics, as well as a commitment to advancing their skills and knowledge in these areas, are typically encouraged to apply.

, Organizations Involved in Genomics Research or Applications

Career Supporting Skills

NGS Data Analysis Transcriptome Analysis Epigenetic Analysis Metagenomics De novo Assembly Bioinformatics Tools and Pipelines

Program Outcomes

Participants will gain a comprehensive understanding of NGS data analysis and the ability to apply advanced techniques to real-world research problems.
Participants will become proficient in using popular bioinformatics tools and pipelines for NGS data analysis, enabling them to conduct high-quality and reproducible analyses.
Participants will gain hands-on experience in working with real-world datasets and applying NGS data analysis techniques to solve scientific questions.
Participants will be able to analyze and interpret complex NGS data, including identifying genetic variants, performing differential gene expression analysis, and analyzing epigenetic modifications.
Participants will develop critical thinking and problem-solving skills, enabling them to solve complex problems related to NGS data analysis and apply these skills in real-world research settings.