Algorithms for DNA Sequencing – Online Course

2. September 2015 at 08:48

Start: 5th October 2015 – online course by the John Hopkins University.John_Hopkins_University_banner

About the Course

DNA sequencing is now a ubiquitous tool in life science. You can observe this trend just by reading the news. This course examines the computational problems that come with this onslaught of DNA sequencing data. How do we take a huge collection of DNA “puzzle pieces” and assemble them into a genome? How do we make it quick and easy to find a DNA “needle” in an enormous genomic “haystack”? We will spend the bulk of the course understanding the algorithms and data structures that underlie software tools for analyzing sequencing data. The course is also an opportunity to practice programming skills and gain exposure to basic algorithms and data structures.
This course has a $99 value but is being offered at a significant discount.

Creation of this course was supported by the Department of Computer Science at JHU and by National Science Foundation Grant IIS-1349906.

Course Syllabus

Sequencing
– Introduction to DNA sequencing
– Second-generation sequencing and parsing sequencing reads

Computational problems
– Read alignment
– De novo assembly

Exact matching
– Strings
– Exact matching problem and naive algorithm
– Boyer-Moore

Preprocessing
– Online versus offline algorithms
– Indexing
– Multimaps, binary search, hash tables

Approximate matching
– Pigeonhole principle
– Hamming and edit distance
– Global and local alignment

De novo assembly
– Overlaps
– Shortest common superstring and greedy algorithm
– De Bruijn graphs
– How practical assemblers work

Recommended Background

You should be comfortable programming in Python, or be willing and able to learn as you go. Some undergraduate-level computer science background is helpful but not necessary. No background in biology or genomics is necessary.

Suggested Readings

There is no required textbook for the class and all materials will be provided.

Course Format

Course content comes in a few flavors:

– About 1 hour of lectures per week by Prof. Langmead
– About 1 hour of practical lectures per week by Prof. Langmead and Jacob Pritt,
where we show and discuss implementations of ideas from the technical lectures
– One multiple choice homework assignment per module (4 total)
– One programming-based homework assignment per module (4 total)
– Some optional lectures covering a broader selection of research ideas

 

For more information about this course visit their website here.

 

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