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STAT718/BIO703

Fall 2024

Genomic Data Science

Instructor: Yen-Yi Ho

Office: LeConte 216A

Class Meetings:

Monday/Wednesday/Friday 9:40AM - 10:30AM

Classroom: LeConte 206

Dr. Ho's office Hours: Thursday afternoon 16:00-17:30PM, Friday afternoon 14:00-15:00 PM or by appointment (LeConte 216A)

Email: hoyen@stat.sc.edu

Teaching Assistant: Kaniz Fatema (KFATEMA@email.sc.edu)

TA office hours: MW 12:30PM-2PM, Tuesday 11:30PM-1PM, LeConte 111

Textbook:

1. Introduction to Data Science: Data Wrangling and Visualization with R by Rafael A. Irizarry (Required)

2. Cedric Gondro (2015). Primer to Analysis of Genomic Data Using R.

3. Wim P. Krijnen. Applied Statistics for Bioinformatics Using R. November 2009.

4. Avril Coghlan. A Little Book of R for Bioinformatics. Release 0.1. Aug18, 2017

6. Hahne, Huber, Gentleman, and Falcon (2008): Bioconductor Case Studies

Resources:

1. This is Statistics.org

2. Bioconductor

Annoucements:

Approximate course outline: (Lecture notes will be updated often)

Acknowledgement: The contents of this course are developed based on the book "Introduction to Data Science by Rafael A. Irizarry, RNA-seq workflow on the Bioconductor website and the Harvard Chan Bioinformatics Core.

Date	Weekly topic	Homework	R code	Reading
Week Aug 19	Syllabus Getting Started with R and R Studio R Markdown (Chapter 20.2 in Rafa)	Homework 1 Homework Template Rmarkdown cheat sheet		Chapter 1 (Irizarry) Chapter 20 (Irizarry) Chapter 2 (Irizarry)
Week Aug 26	Chapter 2: R Basics Very Basics Data Types Vectors Coercion Not availables (NA) Sorting Vector Arithmetics Indexing Basic plots	Homework 1 Due (Aug 30 before class) Homework 2	R-Basics1.R Link for Requesting HPC account (Choose Research Computing Account creation)	Chapter 3 (Irizarry)
Week Sep 02	Sep 04: Labor Day R Basics 2 Getting Data Into R Getting Results Out of R Chapter 3: Programming Basics Conditional Expressions Defining Functions Namespaces For-loops Vectorized Functions	brainbod.txt brainbod1.txt brainbod.csv	R-Basic2.R ALLcode.R programming-basics.R programming-basics_9_13.R	Chapter 4 (Irizarry) Chapter 5 (Irizarry)
Week Sep 09	Chapter 3: Programming Basics Conditional Expressions Defining Functions Namespaces For-loops Vectorized Functions	Homework 2 Due (Sep 13 before class) Homework 3 AA.txt	RcodeInClass9_9.R programming_basic_9_18.R	Chapter 7 (Irizarry) Chapter 8 (Irizarry)
Week Sep 16	Data Visualization Principles FlowingData Data Exploration Through Time	Homework 3 Due (Sep 27 before class) Homework 4	tidyverse.R Visualization ggplot2 ggplot2 cheat sheet	Chapter 9 (Irizarry) Chapter 10 (Irizarry)
Week Sep 23	Introduction to RNAseq Methods and Experimental Design What is "n" is cell culture experiments? Confounding Effect	Homework4 Due (Oct 4 before class)	raw-Counts.tsv experiment-design.tsv
Week Sep 30	RNAseq Quality Assessment RNAseq Alignment	Final Project Instruction Final Project Proposal Template Homework 5	RNAseqAlignment.R RNAseqAlignment2.R
Week Oct 07	Count normalization with DESeq2 DGE QC Analysis	Homework 5 Due (Oct 16 before class) Homework 6	DGE_QC.R DESeq2-Rcode.R
Week Oct 16	Gene-Level DE Analysis Gene-Level DE Analysis II	Homework 6 Due (Nov 8 before class) Homework 7 targets.txt		Reading List for NGS Chap 3 (Bioconductor) Chap 6 (Krijnen)
Week Oct 14	Multiple Comparisons Functional Analysis		FunctionalAnalysis.R	Chap 6 (Gondro) Chap 6 (Bioconductor)
Week Oct 21	Single-Cell RNAseq Data Analysis	Final Project Proposal Due (November 11 Before Class) Homework 7 Due (November 16 at 5PM)	HPC tutorial Linux Commands Linux File Transfer test.R test.sh	Chap 6 (Gondro)
Week Oct 28	Single-Cell RNAseq Data Analysis II
Week Nov 04	Single-Cell RNAseq Data Analysis III		Download FASTQ file from SRA RNAseq.fastq rna_1_1.fq.bz2 rna_2_1.fq.bz2 Bowtie and Samtools
Week Nov 11	Single-Cell RNAseq Data Analysis IV	Final Project Template Final Project format	test.R test.sh
Week Nov 18	Student Presentation
Week De 02	Student Presentation	Final Project Due December 11, 2024 Wed before 5PM (EST)