Duke HTS 2017

Week 1

General

• High-Throughput Sequencing Course Welcome
• 2017 High-Throughput Sequencing Course: Final Schedule

Statistics

• Introduction to Statistics
• Introduction to Statistics (Handout)
• Statistical Inference: Part I
• Statistical Inference: Part I (Handout)

Computation

• Duke HTS Summer Course 2017 - Computational Bootcamp
• Introduction to R
• Custom Functions in R
• Mapping with apply
• Cleaning and preparing data
• Main Additions and Modifications to Traditional R.
• Manipulating Data
• Friday Morning Exercises
• Solutions to Friday Morning Exercises

Biology

• RNA-Seq Sample Preparation Theory

Week 2

Computation

• Warm-up exercises
• Solutions to Warm-up exercises
• Monday Morning Exercises
• Solutions to Monday Morning Exercises

Biology

• Molecular Biology Lab Intro
• Ribo-Zero Protocol
• Protocol for NEBNext Ultra Directional RNA Library Prep Kit
• magnetic_bead_MSDS.pdf
• manualE6609.pdf
• manualE7420_v8.pdf
• ribo-zero-reference-guide-15066012-02.pdf
• RNACleanConcentrator5_ver2_2_1.pdf

Week 3

Statistics

• Experimental Design Part I
• Experimental Design Part II
• RNA-seq: technical variability and sampling
• RNA-seq: An assessment of technical reproducibility and comparison with gene expression arrays
• Statistical Estimation
• Statistical Estimation (Handout)
• Sources of Variability
• Sources of Variability (Handout)
• Unsupervised Learning
• Unsupervised Learning (Handout)
• Supervised Learning
• Supervised Learning (Handout)
• RPC
• ROC (Handout)

Computation

• Statistical Inference
• Statistical Estimation
• Sources of Variability
• Unsupervised Learning
• Supervised Learning
• Regression

Week 4

Statistics

• Count Models
• Count Models (Handout)
• Gene Networks
• Gene Networks (R script)
• Gene Networks (Data files)

Bioinformatics

• Bioinformatics Overview

• Counting Reads
• Demultiplex a Raw FASTQ
• Raw Data
• Introduction to FASTQ Files
• What do quality scores mean?
• Trimming and Filtering a FASTQ
• Trimming and Filtering
• Quality Control
• Demultiplexing 2015 Data
• Working with Multiple Samples
• Working with Multiple Samples
• Prepare Data
• Downloading Everything
• Using IGV
• Working with Multiple Samples
• Mapping Reads to a Reference Genome
• Mapping with Tophat
• Working with Paired-Reads
• Working with Paired-Reads
• What do quality scores mean?

Computation

• Review
• Review: Solutions
• Using ggplot2
• Using ggplot2: Solutions
• Receiver Operating Characteristic
• Count Models
• Count Models: Solutions
• The Unix Shell: File and Directory Management
• The Unix Shell: Working with Text
• The Unix Shell: Finding Stuff
• The Unix Shell: Regular Expressions
• The Unix Shell: Writing Shell Scripts
• The Unix Shell: Exercises
• The Unix Shell: Exercises with Solutions
• Computing capstone exercise
• Computing capstone exercise: Solutions

Week 5

Statistics

• Time Course
• Time Course (Handout)
• Censoring
• Censoring (Handout)
• Setting up an RNA-Seq pipeline

• Introduction to DESeq2
• DESeq2 Analysis of 2015 Data
• STAR: Pipeline
• GATK: Prepare Reference Files
• GATK Pipeline for calling variants from one sample

Bioinformatics

• Data Standards
• Data Sharing Provenance
• Clinical Terminologies
• Ontology
• Short Read Alignment

Week 6

Analysis of RNA-seq data

• Reference Genome and Annotation
• Adapter
• Data Overview
• HTS Course: DESeq2 Analysis Outline for 2017 Pilot Data
• DESeq2 Analysis of 2015 Data