Genomics 1
Why study genomics?
Genomics is an essential subfield of bioinformatics, and a major force in expanding human knowledge of genetic associations with disease and other traits. It is an interdisciplinary field, including the development of methods for DNA sequencing, as well as for big data analysis of genomic sequences. Next-Generation Sequencing (NGS) techniques allow for whole-genome sequencing, and analysis of epigenetic factors such as DNA-protein interactions and DNA methylation with unprecedented efficiency. Massive databases for biological sequence data such as GenBank (National Center for Biotechnology Information), EMBL (European Bioinformatics Institute), and SRA allow for data-driven research and knowledge discovery. Large amounts of data such as from the 1000 Genomes Project are publicly available, providing anyone with the proper analytical skills and resources the opportunity for scientific discovery. While transcriptomics seeks to find variation in gene expression through methods such as RNA sequencing, genomics studies genome-wide genetic variation at the fundamental level of DNA sequences. The understanding of genetic associations provided by genomic research have great value in medicine, agriculture, ecology, biotechnology, and many other industries.
Course description
This course serves as an introduction to the bioinformatics sub-discipline of genomics. Students will be familiarized with the biology of genetics and genetic variation, while considering practical applications of genomics to research and medicine. An example analysis of real-world NGS data is then provided in a tutorial, offering students the chance to employ state-of-the-art genomics algorithms using the T-BioInfo platform. Students will load NGS data, and construct a data analysis pipeline within the platform to identify genetic variants associated with breast cancer.
Student will need access to the T-BioInfo platform to follow the provided data analysis tutorial. Access can be obtained by emailing a request to info@pine-biotech.com. Account information is typically issued within 24 hours of the request. The tutorial also incorporates the Integrative Genomics Viewer, a freely available visualization tool for large-scale genomic data. Integrative Genomics Viewer must be installed locally to perform the analysis detailed in the practical tutorial section of the course.
Course Features
- Lectures 7
- Quizzes 2
- Duration 6 hours
- Skill level All levels
- Language English
- Students 823
- Certificate Yes
- Assessments Yes
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Introduction to Genomics
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Practical Tutorial: Variant Calling Pipeline
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Supplementary Resources
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Subhrajit Barua
Amazing clarity of Concept imparted!
Genomics1 is my favourite course on tbio-info as it elegantly answers the question - What is genomics? This course clarifies the much-debated ambiguity between genetics and genomics. These two terms are often confused and wrongly used. The course then moves on to explain the most important concept of central dogma and the biological significance of genome. It also covers the various types of Genomic variations like duplication, inversion, deletion, translocation, substitution, etc. We encounter the algorithms on Pre-processing of data, Mapping, Variant calling and Annotations. We get to run a pipeline on our own using the Variant Calling algorithm – Strelka.
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Pratim Chakraborti
A good starting course
The Genomics Course starts with a generic introduction comprising the basics of the central dogma, the pivotal concept of Molecular Biology. After the bare essential theories are over, the turn to use the Pipelines (t-bio server) comes. The best thing about the course is that it brings out the perfect flavour of a how a pipeline should be used and leave the ground open for further explorations by the participant to click and use the other sets of algorithms at the “t-bio server” on “Data Pre-Processing”, “Mapping”, “Variant Calling”, “Annotation”. Subsequent to the execution of the sample pipeline comes the analysis of the results, and here also the course leaves the ground open for the initiated participant for exploring more beyond what is being explained. It also provides a link to a carefully developed sample project using Machine Learning present at the Edu site. Carefully curated Quiz, benchmark the learning path. The list of references at the end provides the user pointers for further reading.
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sumitkumar
Short yet descriptive
If you have a little knowledge of cell cycle and central dogma you are good to go with this course. I get to know about Variant Calling Analysis which is the main topic of this course other than basics of genomics. I thoroughly enjoyed the content, and you guys have made it sound as simple as possible.
