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AKTU NGS Technology and Data Analysis (HTCB701) Syllabus PDF – B.Tech Honors Degree in Computational Biology and Bioinformatics
NGS Technology and Data Analysis HTCB701
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Official AKTU syllabus of NGS Technology and Data Analysis (HTCB701) for B.Tech Honors Degree in Computational Biology and Bioinformatics – 4 credits, L-T-P 3-1-0. Read the unit-wise course content, course outcomes, evaluation pattern and recommended books online, or download the PDF.
Syllabus — NGS Technology and Data Analysis
Download PDFHTCB701 · 4 credits · L-T-P 3-1-0
Course Outcomes
| Course Outcome | Description At the end of the course, the student will be able to |
| CO1 | Understand basic concepts of DNA sequencing and NGS technology. |
| CO2 | Understand the methods of DNA sequencing and NGS technology. |
| CO3 | Explain the process of RNA sequencing. |
| CO4 | Understand concepts of ChiPSeq. |
| CO5 | Analyze differentially expressed data and NGS applications. |
| Detailed Syllabus (Theory) | |
| Unit No. | Topics CO No. No. of proposed lectures |
| I | Introduction: High throughput sequencing, Basic concept and applications of NGS technology, Various methods NGS technology, Recent advancements using NGS technology, Data types, Data formats ,Data processing, Data analysis, Data evaluation, Data visualization. Genome sequencing and Protein sequencing. Genetic variations and genetics of complex disease. Non-synonymous and Synonymous variants, Regulatory variants and Statistical methods on rare variants. 1 8 |
| II | DNA Sequencing : Whole genome sequencing, Sanger sequencing, Maxam Gilbert sequencing, Target sequencing, Pool sequencing, Sequencing mappability, Refined alignment, Base quality recalibration ,Variants identification for Diploid genome, Next generation sequencing technologies (Illumina (Solexa), Ion Torrent, Roche 454, SOLiD and Pac Bio) Short read assembly, alignment and applications; gene expression analysis. 2 8 |
| III | RNA Sequencing: Biological theories on RNA seq experiments, Case studies for experimental consideration, Scientific advancements using RNA seq, Differential expression analysis, Alternative splicing, Transcript variation, Allele-specific expression ,RNA editing and smRNA. 3 8 |
| IV | ChiPSeq: Biological theories on ChIPseq analysis, Case studies for experimental considerations, DNA fragment evaluation, Peak identification, Two condition comparison, Saturation analysis, Motif finding and related theories, DNA methylation, Case studies for statistical considerations, Related Bioinformatics tools, Histone modification and Hidden Markov model annotating histone marks. 4 8 |
| V | Analysis: Using RNA seq, Data to Detect Differentially Expressed Genes, Differential Expression Analysis of Complex RNA seq Experiments Using edger, Design of RNA Sequencing Experiments, small RNA sequencing. Functional PCA differential expression testing using RNA seq data. Statistical Analysis study of Rare Variants. NGS applications in Agri-Biotech, health care, metagenomics, GWAS and basic sciences. 5 8 |
Text Books
- Somnath Datta,Nettleton Dan (Eds.)Statistical Analysis of Next Generation Sequencing Data.
- Stuart M. Brown. Next-Generation DNA Sequencing Informatics.
Reference Books
- Ali Masoudi-Nejad, Zahra Narimani, NazaninHosseinkhan. Next Generation Sequencing and Sequence Assembly.
- Methodologies and Algorithms (SpringerBriefs in Systems Biology), ISBN-10: 1461477255, Springer.
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