Home Page  • Contact email

Applied Bioinformatics (2020)

Your progress in the course: 0%

The purpose of this course is to introduce students to the various applications of high-throughput sequencing including RNA-Seq, SNP calling, de-novo assembly and others.

The course material will concentrate on presenting data analysis scenarios for each of these domains of applications and will introduce students to a wide variety of existing tools and techniques.

The course will run between Aug 24- Dec 13, 2020

Note: The tests were intended to be quite difficult, substantially more challenging than the typical homework assignments. Each question was designed to probe a deeper and more profound understanding of the subjects.

We recommend forming small study groups to discuss each question. You may learn quite a bit from hearing how others think. Answers may be submitted an unlimited number of times but successive submissions must be at least one hour apart.

Some questions/answers may end up being a little subjective with different valid interpretations, we are working on identifying and reformulating these.

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

Test
Lecture 9: Sequence format FASTA and FASTQ

Understand sequence representation data formats

Test
Lecture 10: Quality control of sequencing data

How to evaluate and improve sequencing data quality

Test
Lecture 11: How to write Unix data analysis scripts

Learn to automate data analysis with reusable scripts

Test
Lecture 12: How to get better at writing data analysis scripts

Learn how to read code, how to use recipes to get started

Test
Lecture 13: Sequencing concepts

How do sequencers work. Sequencing coverage. How much data do we need.

Test
Lecture 14: Sequence alignments

Introduction to sequence alignments, alignment scoring, local, global and semi-global alignments

Test
Lecture 15: BLAST, Basic Local Alignment Search Tool

Learn to use BLAST at the command line, build BLAST databases, learn to customize BLAST

Test
Lecture 16: Short Read Alignment

Learn to perform high throughput sequencing data alignment.

Test
Lecture 17: Sequence Alignment Maps (SAM/BAM)

What information does a SAM file contain.

Test
Lecture 18: Visualizing and interpreting BAM files

Understand how to visually evaluate high throughput sequencing data alignments.

Test
Lecture 19: Large Scale Genomic Variation

How to do insertions, deletions, copy number variations appear in high throughput sequencing data

Test
Lecture 20: Working with BAM files.

How to filter and process BAM files from command line.

Test
Lecture 21: Variant (SNP) calling from short reads

How to call SNPs and short variations from sequencing reads

Test
DRAFT
Lec 22

todo

DRAFT
lec 23

todo

DRAFT
Lec 24

todo

DRAFT
Lec 25

todo

DRAFT
Lec 26

todo