/OMICS

Drexel Medicine OMICS course

Primary LanguagePythonGNU Affero General Public License v3.0AGPL-3.0

Drexel Medicine Advanced OMICS

MIIM-620S Blackboard (Bb) Learn course site

  1. Course
  2. Layout
  3. Schedule
  4. Projects
  5. Grading
  6. vim, a powerful editor used by coders on the commandline

Course

Course Description

Recent advances in molecular biology and computational achievements have generated an explosion of data that surveys biological processes on a massive scale. Collectively referred to as ‘omics scale data, these techniques have revolutionized our ability to explore complex phenotypes in microbiology & immunology. This course covers the history, application, and computational analysis of ‘omics scale data and provides hands-on analysis experience.

Course Objectives

  1. Recognize popular next-generation sequencing technologies and distinguish their appropriate uses.
  2. Recognize how to apply OMICS scale techniques to multiple facets of microbiology and immunology.
  3. Design OMICS scale experiments to inspect biological functions across DNA, RNA, and proteins.
  4. Perform basic terminal activities such as moving, copying, inspecting files, and calling installed tools as well as employ pipes to chain small functions together to create complex analyses.
  5. Utilize Jupyter Notebooks to perform data analysis and visualization of OMICS scale data.
  6. Practice presenting OMICS scale data analysis to both traditional & computational biological audiences.

Faculty Team

Instructor ABC Role
Dr. Will Dampier WND Co-Director, Instructor
Dr. Joshua Earl JPE Instructor
Dr. Katherine Innamorati KAI Instructor
Dr. DV Klopfenstein DVK Instructor
Dr. Joshua Chang Mell JCM Co-Director, Instructor

Major Learning Activities

Name Grade Description
Class Participation 25% Participation in weekly lecture and in-class learning activities.
Weekly Assignment 50% Completing weekly assignments
Project 25% Weekly analysis of your own dataset

Repository Layout

This repository contains all of the learning content for the course and will be the way you submit all assignments.

The content folder contains the learning content organized by week. You will pull this from the main repository each week.

Within each week's assignment you will be asked to create a notes_{github-user}.md file as you complete the assignments in each week's folder. As you complete the assignment you will commit these notes and when complete, make PRs to the main repository. This is how you will submit assignments.

The projects folder contains information about the ongoing project and is where you will keep information and notes.

Weekly Schedule

Week Date Module Topic Instructors Status
1 08/22/2023 Hello World Course intro, git, & JupyterHub DVK, KAI released
2 08/29/2023 Hello World Terminal + git: push & "Pull Requests" DVK, KAI released
3 09/05/2023 Hello World Sequencing datasets & terminal analysis WND, JCM released
4 09/12/2023 Align all the things NGS read alignment WND, JCM released
5 09/19/2023 Align all the things Counting aligned reads WND, JCM released
6 09/26/2023 Align all the things Variant calling WND, JCM released
7 10/03/2023 Align all the things Interpreting variant effects WND, JCM released
8 10/10/2023 OMICS as count table Transcriptomics WND, JCM released
9 10/17/2023 OMICS as count table Statistical Analysis of Count-Data WND, JCM released
10 10/24/2023 OMICS as count table Introduction to the powerful vim editor DVK released
11 10/31/2023 OMICS as count table Gene Ontology Enrichment Analysis DVK released
12 11/07/2023 OMICS as count table Peak analysis in OMICS data (ChIP-Seq) WND, JCM unreleased
13 11/14/2023 Genome Comparisons Microbiome creation JPE, KAI unreleased
14 11/21/2023 Genome Comparisons Microbiome analysis JPE, KAI unreleased
15 11/28/2023 Genome Comparisons Microbiome metrics JPI, KAI unreleased
16 12/05/2023 Future directions in OMICS Everyone unreleased

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