HTS2019

Slides

  • Slide sets
    • Background knowledge of HTS2019
    • Wet Lab
    • Bioinformatics
    • Biostatistics

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
HTS2019
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  • Slide sets
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Slide sets¶

Background knowledge of HTS2019¶

  • HTS background

  • Library preparation

  • Welcome slides

Wet Lab¶

  • Introduction to Molecular Biology

  • RNaseH Depletion of rRNA

  • NEBNext® Ultra II Directional RNA Library Prep Kit for Illumina®

  • Working with RNA: the basics

  • Post lab review

Bioinformatics¶

  • Bioinformatics overview

  • Welcome slides

  • Short Read Alignment

  • Microbiome Analysis

Biostatistics¶

  • Introduction handout

  • Introduction

  • Statistical Inference I handout

  • Statistical Inference I

  • Statistical Inference II handout

  • Statistical Inference II

  • Unsupervised Learning handout

  • Unsupervised Learning

  • GLM models handout

  • GLM models

  • Count Models handout

  • Count Models

  • Source of variability handout

  • Source of variability

  • Gene set analysis

  • Multiple Testing

  • Networks

  • Composition

  • Time Course handout

  • Time Course

  • Interactions handout

  • Interactions

  • Ontology

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