GEN242
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About
Introduction
Syllabus
Schedule
Internal
Resources
Installation
Slides
Course Introduction (S1)
Genome Basics (S2)
Databases and Software (S3)
Git and GitHub (S4)
Linux Cluster Basics (S5)
DNA Sequencing (S6)
Introduction to R (S7)
Sequence Alignments (S8)
Programming in R (S9)
Multiple Alignments (S10)
Short Read Alignments (S11)
R on HPC (S12)
NGS Analysis Basics (S13)
Gene Expression Analysis (S14)
NGS Workflows (S15)
Cluster Analysis (S16)
Enrichment Analysis (S17)
ChIP-Seq Overview (S18)
VAR-Seq Overview (S19)
Project Data (S20)
Graphics in R (S21)
Tidyverse and SQLite (S22)
Building R Packages (S23)
Workflow Review (S24)
CWL (S25)
Final Discussion (S26)
Additional Slide Shows (S27)
Tutorials
GitHub Introduction (T1)
Linux and HPCC Cluster (T2)
Introduction to R (T3)
Programming in R (T4)
Parallel R (T5)
NGS Analysis Basics (T6)
Workflows (T7)
RNA-Seq Workflow (T8)
Cluster Analysis and Data Mining (T9)
Functional Enrichment Analysis (T10)
ChIP-Seq Workflow (T11)
scRNA-Seq Embedding Methods (T11)
VAR-Seq Workflow (T13)
R Markdown (T14)
Project Data (T15)
Graphics and Visualization (T16)
Shiny Apps (T17)
Tidyverse and SQLite (T18)
Building R Packages (T19)
Automate CWL Creation (T20)
Assignments
Homework
HW1: Intro & GitHub
HW2: Linux & HPC
HW3: R Basics
HW4: Alignments
HW5: R Programming
HW6: NGS Analysis Basics
HW7: RNA-Seq Analysis
HW8: R Markdown
Projects
Overview of Projects
RNA-Seq Aligners
DEG Methods
DET Methods
Cluster Analysis
scRNA-Seq Embedding
ChIP-Seq Peak Callers
Functional Enrichment
Motif Enrichment*
Genome Graphics*
Drug-target Analysis
lncRNA Discovery
Variant Callers
Project Data
Presentations
Paper Presentations
Links
Piazza
GitHub Classroom
GitHub Repo
Bioconductor
Hugo, Docsy & R
News
Slides
Course Introduction
Genome Basics
Databases and Software
Git and GitHub
Linux and Cluster Basics
DNA Sequencing
Introduction to R
Sequence Alignments
Programming in R
Multiple Alignments
Short Read Alignments
R on HPC
NGS Analysis Basics
Analysis of Gene Expression Data
Introduction to NGS Workflows
Cluster Analysis
Functional Enrichment Analysis
ChIP-Seq Analysis
VAR-Seq Analysis
Project Data
R Graphics
R packages
dplyr, tidyr and SQLite
Review of Data Analysis Workflows
Structure and Auto-Generation of CWL Parameter Files
Additional Slide Shows
Final Discussion
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Slides
Introduction to R
Introduction to R
1 minute read
Will be added shortly before lecture.
Last modified 2025-03-26:
some edits (842d226af)