This course is all about diving into the world of high-throughput sequencing. We'll cover a lot, from RNA-Seq to SNP calling, de-novo assembly, and more. Get ready to explore real-world scenarios for these applications, and discover a bunch of tools and techniques that bioinformaticians use every day.
Mark your calendar: The course kicks off on August 21st, 2023, and wraps up on December 9, 2023. You can look forward to new lectures every week.
Note: The lectures will include associated tests, which are intentionally more demanding than standard homework assignments. The tests were crafted to dig into your understanding of the topics. Feel free to team up with classmates and form study groups. You'll be surprised how much you can learn from each other's viewpoints. And don't worry about getting the answers just right the first time; you can try again as many times as you like, but remember to wait at least an hour between attempts.
| Lecture | Your Score |
|---|---|
|
Lecture 1: Getting started with Bioinformatics
How is bioinformatics practiced? Computer setup. |
Test |
|
Lecture 2: How to use the command line
How to use Unix? Why is the command line so useful in bioinformatics. |
Test |
|
Lecture 3: Data analysis at the command line
How to process biological data from the command line. |
Test |
|
Lecture 4: What do the words mean?
How to make sense of terminology. Sequence and gene ontologies. |
Test |
|
Lecture 5: Statistics Survival Guide
Terminology and definition for the most commonly used statistical terms. |
Test |
|
Lecture 6: How to interpret a list of genes?
Functional enrichment, functional over-representation. |
Test |
|
Lecture 7: Biological data formats
Learn how information is represented in biology |
Test |
|
Lecture 8: Automating data access
How to automate data access, download genome wide information, download data by accession number |
Test |
|
Lecture 9: Sequence format FASTA and FASTQ
Understand sequence representation data formats |
Test |
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Lecture 10: Quality control of sequencing data
How to evaluate and improve sequencing data quality |
Test |
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Lecture 11: How to write Unix data analysis scripts
Learn to automate data analysis with reusable scripts |
Test |
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Lecture 12: Sequence alignments
Introduction to sequence alignments, alignment scoring, local, global and semi-global alignments |
Test |
|
Lecture 13: BLAST, Basic Local Alignment Search Tool
Learn to use BLAST at the command line, build BLAST databases, learn to customize BLAST |
Test |
|
Lecture 14: Short Read Alignments
Learn to perform high throughput sequencing data alignment. |
Test |
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Lecture 15: Visualizing and interpreting BAM files
Understand how to visually evaluate high throughput sequencing data alignments. |
Test |
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Lecture 16: Sequence Alignment Maps (SAM/BAM)
What information does a SAM file contain. |
Test |
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Lecture 17: Automating with Makefiles
Learn write better scripts, build automated pipelines with make |
Test |
|
Lecture 18: Sequencing concepts
How do sequencers work. Sequencing coverage. How much data do we need. |
Test |
|
Lecture 19: Variant (SNP) calling from short reads
How to call SNPs and short variations from sequencing reads |
Test |
|
Lecture 20: Visualizing Genomic Variation
How to do insertions, deletions, copy number variations appear in high throughput sequencing data |
Test |
|
Lecture 21: Working with BAM files.
How to filter and process BAM files from command line. |
Test |
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Lecture 22: RNA-Seq data analysis
Quantifying gene expression via sequencing |