Course Summary
Learn the fundamentals of DNA sequencing, including technologies, methods, and applications in this beginner-level course.Key Learning Points
- Understand the basics of DNA sequencing and different sequencing technologies
- Gain hands-on experience in analyzing DNA sequencing data
- Explore real-world applications of DNA sequencing in fields such as medicine and agriculture
Job Positions & Salaries of people who have taken this course might have
- USA: $89,000
- India: ₹10,00,000
- Spain: €39,000
- USA: $89,000
- India: ₹10,00,000
- Spain: €39,000
- USA: $66,000
- India: ₹6,00,000
- Spain: €26,000
- USA: $89,000
- India: ₹10,00,000
- Spain: €39,000
- USA: $66,000
- India: ₹6,00,000
- Spain: €26,000
- USA: $56,000
- India: ₹5,00,000
- Spain: €21,000
Related Topics for further study
Learning Outcomes
- Understand the different methods and technologies used in DNA sequencing
- Gain practical experience in analyzing DNA sequencing data
- Apply DNA sequencing in real-world scenarios such as medical research and agriculture
Prerequisites or good to have knowledge before taking this course
- Basic knowledge of biology
- Familiarity with data analysis tools and techniques
Course Difficulty Level
BeginnerCourse Format
- Online self-paced course
- Video lectures
- Hands-on exercises
Similar Courses
- Bioinformatics
- Introduction to Genetics and Evolution
- Genome Sequencing (Bioinformatics II)
Related Education Paths
- Master in Bioinformatics
- Graduate Certificate in Genomics and Data Analysis
- Certificate in Biotechnology
Related Books
Description
We will learn computational methods -- algorithms and data structures -- for analyzing DNA sequencing data. We will learn a little about DNA, genomics, and how DNA sequencing is used. We will use Python to implement key algorithms and data structures and to analyze real genomes and DNA sequencing datasets.
Outline
- DNA sequencing, strings and matching
- Module 1 Introduction
- Lecture: Why study this?
- Lecture: DNA sequencing past and present
- Lecture: Genomes as strings, reads as substrings
- Lecture: String definitions and Python examples
- Practical: String basics
- Practical: Manipulating DNA strings
- Practical: Downloading and parsing a genome
- Lecture: How DNA gets copied
- Optional lecture: How second-generation sequencers work
- Optional lecture: Sequencing errors and base qualities
- Lecture: Sequencing reads in FASTQ format
- Practical: Working with sequencing reads
- Practical: Analyzing reads by position
- Lecture: Sequencers give pieces to genomic puzzles
- Lecture: Read alignment and why it's hard
- Lecture: Naive exact matching
- Practical: Matching artificial reads
- Practical: Matching real reads
- Welcome to Algorithms for DNA Sequencing
- Pre Course Survey
- Syllabus
- Setting up Python (and Jupyter)
- Getting slides and notebooks
- Using data files with Python programs
- Programming Homework 1 Instructions (Read First)
- Module 1
- Programming Homework 1
- Preprocessing, indexing and approximate matching
- Week 2 Introduction
- Lecture: Boyer-Moore basics
- Lecture: Boyer-Moore: putting it all together
- Lecture: Diversion: Repetitive elements
- Practical: Implementing Boyer-Moore
- Lecture: Preprocessing
- Lecture: Indexing and the k-mer index
- Lecture: Ordered structures for indexing
- Lecture: Hash tables for indexing
- Practical: Implementing a k-mer index
- Lecture: Variations on k-mer indexes
- Lecture: Genome indexes used in research
- Lecture: Approximate matching, Hamming and edit distance
- Lecture: Pigeonhole principle
- Practical: Implementing the pigeonhole principle
- Programming Homework 2 Instructions (Read First)
- Module 2
- Programming Homework 2
- Edit distance, assembly, overlaps
- Module 3 Introduction
- Lecture: Solving the edit distance problem
- Lecture: Using dynamic programming for edit distance
- Practical: Implementing dynamic programming for edit distance
- Lecture: A new solution to approximate matching
- Lecture: Meet the family: global and local alignment
- Practical: Implementing global alignment
- Lecture: Read alignment in the field
- Lecture: Assembly: working from scratch
- Lecture: First and second laws of assembly
- Lecture: Overlap graphs
- Practical: Overlaps between pairs of reads
- Practical: Finding and representing all overlaps
- Programming Homework 3 Instructions (Read First)
- Module 3
- Programming Homework 3
- Algorithms for assembly
- Module 4 introduction
- Lecture: The shortest common superstring problem
- Practical: Implementing shortest common superstring
- Lecture: Greedy shortest common superstring
- Practical: Implementing greedy shortest common superstring
- Lecture: Third law of assembly: repeats are bad
- Lecture: De Bruijn graphs and Eulerian walks
- Practical: Building a De Bruijn graph
- Lecture: When Eulerian walks go wrong
- Lecture: Assemblers in practice
- Lecture: The future is long?
- Lecture: Computer science and life science
- Lecture: Thank yous
- Post Course Survey
- Programming Homework 4
- Module 4
Summary of User Reviews
The DNA Sequencing course on Coursera has received high praise from users who have found it to be an excellent introduction to the field. One of the key aspects that many users appreciated was the course's clear and concise explanations of complex concepts.Pros from User Reviews
- Clear and concise explanations of complex concepts
- Engaging and interactive course materials
- Great introduction to the field of DNA sequencing
- Instructors are knowledgeable and responsive to questions
- Hands-on exercises and quizzes reinforce learning
Cons from User Reviews
- Some users found the course to be too basic
- Limited opportunities for interaction with other students
- Some technical glitches reported with course platform
- Could benefit from more in-depth case studies
- Not ideal for those with advanced knowledge in the field
Ben Langmead, PhD
4.7 Raiting
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