Omics Train - Bioinformatics Made Simple

Introduction

Omics Train - Bioinformatics Made Simple

About
About
- Introduction
Programming Languages/Tools
Programming Languages/Tools
- Programming Languages/Tools
- Unix
  Unix
  - Introduction To Shell/Unix
    Introduction To Shell/Unix
    
    Introduction
    
    Navigating Files & Directories
    
    Managing Files & Directories
    
    Redirection and Pipes
    
    Regular Expressions
    
    Shell Scripting
  - Unix Cheatsheet
- R
  R
  - Introduction to R
    Introduction to R
    
    Introduction
    
    Data Types/Variables/Vectors
    
    Data Structures
    
    Functions/Flow
    
    Inspecting/Manipulating Data
    
    Data Vizualization
  - Data Manipulation/Visualization In R
    Data Manipulation/Visualization In R
    
    Introduction
    
    Data Manipulation
    
    Data Visualization
  - R Cheatsheet
- Python
  Python
  - Introduction to Python
    Introduction to Python
    
    Introduction
    
    Variables/Data Types
    
    Libraries/Data Frames
    
    Plotting Data
    
    Lists
    
    Loops/Conditionals
    
    Functions/Scope
  - Conda Environments
- Misc
  Misc
  - Github
  - API
Omics
Omics
- Omics
- Genomics
  Genomics
  - Variant Calling in Cancer
    Variant Calling in Cancer
    
    Introduction
- Transcriptomics
  Transcriptomics
  - Bulk RNA-Sequencing
    Bulk RNA-Sequencing
    
    Introduction
    
    Setup
    
    Quality Control
    
    Read Alignment
    
    Gene Quantification
    
    Differential Expression
  - Single Cell RNA-Sequencing
    Single Cell RNA-Sequencing
    
    Introduction
    
    Setup
  - WGCNA
    WGCNA
    
    WGCNA Pipeline
- Epigenetics
  Epigenetics
  - ChIP-Seq Analysis
    ChIP-Seq Analysis
    
    Introduction
- Proteomics
  Proteomics
  - Labelled Proteomics Data Analysis
    Labelled Proteomics Data Analysis
    
    Introduction
- Metagenomics
  Metagenomics
  - 16S Amplicon Sequencing
    16S Amplicon Sequencing
    
    Introduction
- Epidemiology
  Epidemiology
  - Study Design
    Study Design
    
    Introduction
- Multiomics
  Multiomics
  - Cannonical Correlation Analysis
    Cannonical Correlation Analysis
    
    Introduction
Biostatistics
Biostatistics
- Biostatistics
- Setup
- Biostatistics Cheatsheet
- Variables and Sampling
  Variables and Sampling
- Analyzing One Categorial Variable
  Analyzing One Categorial Variable
  - Binomial Test
- Analyzing Two Categorical Variables
  Analyzing Two Categorical Variables
- Analyzing One Numeric Variable
  Analyzing One Numeric Variable
  - One Sample T-Test
- Analyzing Numeric Variable With Two Groups
  Analyzing Numeric Variable With Two Groups
  - Paired T-Test
  - Two Sample T-Test
- Analyzing Two Numeric Variables
  Analyzing Two Numeric Variables
  - Correlation
- Analyzing Two Or More Groups
  Analyzing Two Or More Groups
  - One-Way ANOVA
Machine Learning
Machine Learning
- Machine Learning
- Tutorial Setup
- Unsupervised Learning
  Unsupervised Learning
- Supervised Learning
  Supervised Learning

Omics Train

The aim of Omics Train is make bioinformatics concepts digestible and the application of techniques clear. We will break down topics using the following categories:

Programming Languages/Tools: tutorials in Unix, Python and R
Omics: covers omics level analyses (RNA-seq, GWAS, Proteomics, etc.)
Biostatistics: basics of how to analyze numeric/categorical data
Machine Learning: how to leverage machine learning to solve questions in biological data