Applied-Genomic-Technologies

Final Paper Submission 2022Fall

To submit the final project, please follow these steps:

1. To start, fork this repository. Fork a repo - GitHub Docs
2. Clone the repository to your computer.
3. Upload your files and commit changes to complete your solution.
4. Push/sync the changes up to GitHub.
5. Create a pull request on the original repository to turn in the assignment. Creating a pull request - GitHub Docs

Tips: You can install Github Desktop to use GUI instead of command line.

Requirements:

1. Please put the final paper of your group in the "Final_Paper" Folder in this repository. Create a folder and put your paper .md files together with figures within the folder.
2. The name of the Folder should be "Group_Number_Topic". e.g. "Group_1_RNA-seq".
3. The final paper is the “class handout” you would give to your future class who attend your mini-lecture. Please use the chapters of 3D Genome Book as examples of a final paper. An outstanding final paper should read like a book chapter or a section of a book chapter for a future textbook.

Grading:

The final paper will be graded by the 3 TAs. Each TA will give a score in 1-10 to each paper. The average score will be the score of this final paper of this team. All team members will receive the same score.

Acknowledgments

We thank BENG183 alumni: John David Lin, Samuel Beppler, Paige Dubelko, Pericles Corkos, Elisha Beebe, Mengyi Liu, Kelsey Dang, Katy Zou, Diego Quintero, Derek Jow, Victoria Tom, Joey Sun.

Chapter1 Molecular Biology

• Review of Molecular Biology from 3D Genome ebook.

Chapter2 DNA sequencing

• Sequencing technolegies from 3D Genome ebook.

Chapter3 RNA sequencing and data analysis

• 3.1 Overview of RNA sequencing
• 3.2 Quantification of gene expression from 3D Genome ebook
• 3.3 Detection of differentially expressed genes from 3D Genome ebook
• 3.4 Single-cell transcriptomic analysis

Chapter4 ChIP-seq and data analysis

• 4.1 ChIP-seq

Chapter5 Introduction to precision medicine

• 5.1 An overview of precision medicine
• 5.2 Precision medicine in breast cancer
• 5.3 Precision medicine in diabetes
• 5.4 An overview of bioinformatic methods for precision medicine

Chapter6 Introduction to hypothesis testing

• 6.1 The instructor’s cheat sheet to hypothesis testing

Chapter7 Machine Learning

• 7.1 Intro to Machine Learning

Appendix: hands-on tutorials

• 1. Data files
• 2. Getting started with the Linux environment
• 3. Working with raw RNA sequencing data
• 4. Mapping RNA-seq reads and quantifying gene expression
• 5. Identifying differentially expressed genes
• 6. A tutorial for writing markdown (.md) files