HTS2019

Slides

Slide sets

Quick Intro of Analysis Tools

Duke HTS Summer Course 2019
Introduction to Unix and bash
Introduction to R
R libraries and Bioconductor
Hands-On Tidyverse - with count data
Simulations and Statistical Inference
Estimation and Hypothesis Testing

Unix Shell

Working with Unix
File I/O
File archival and recovery
Working with text
Unix Variables
Using bash in bioinformatics
Unix capstone exercise
Unix capstone exercise
The Unix Shell: Regular Expressions
Unix Review of Basics

R Graphics and Data Manipulation

Basics of R (Review)
Basics of R (Review)
Data Manipulation in the tidyverse
Tidy Data
File I/O
Unsupervised Learning
Unsupervised Learning
R Graphics
R Graphics
R Graphics
R Graphics Exercise
R Graphics Exercise (Solutions)

Bioinformatics (FASTQ, FASTQC, STAR, etc)

Introduction to FASTQ Files
What do quality scores mean?
What do quality scores mean?
Quality Control
Trimming and Filtering a FASTQ
Trimming and Filtering
Download and Index Genome
Counting Reads
Mapping Reads to a Reference Genome
Making Generic Commands
Making a Pipeline
Working with Loops
Working with Loops
Looping with Globs
Initialize Variables and Make Directories
Make adapter file
Download and Index Genome
Prepare Data
Downloading Everything
Using IGV
Run with shorter intron limit

Analysis of Pilot Data (Gene Count, DESeq2 & DE Analysis)

Get Star Count of the Pilot 2019 Data
DESeq2: Create count matrix and metadata data frame
DESeq2: Create Data Objects
DESeq2: Basic Differential Expression (DE) analysis
DESeq2: Basic Differential Expression (DE) analysis
Generate figures from DESEq2 analysis

Reproducible Analysis (Git)

Data handling Demo
Git Lesson
Git in class

After the course... (Docker & Singularity)

Overview
High Priority
Maintaining Personal Files
Accessing Course Material
Docker Containers
Select Duke Computing Resources
Assorted Notes on Approaches to Reproducible Analysis

HTS2019

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