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NGS Analysis

learn.gencore.bio.nyu.edu

Topics

  • Next-Generation Sequencing Analysis Resources
  • Pre-Requisites
    • Intro to R
    • Introduction to Linux
      • Linux Exercise
      • Nano Tutorials
  • NGS Sequencing Technology and File Formats
    • How Sequencing Works
    • FastA Format
    • FastQ Format
    • Quality Scores
    • SAM/BAM/CRAM Format
    • BED Format
    • VCF Format
    • GFF3 Format
  • Alignment
    • Trimming with Trimmomatic
  • Visualization
  • Variant Calling
    • Pre-Processing
    • Variant Discovery
  • RNA-seq Analysis
    • Aligning RNA-seq data
    • Introduction to R
    • DESeq
    • DESeq 2
    • Gene Set Enrichment Analysis with ClusterProfiler
    • Over-Representation Analysis with ClusterProfiler
    • Salmon & kallisto: Rapid Transcript Quantification for RNA-Seq Data
    • Instructions to install R Modules on Dalma
  • HPC
    • Resources for editing files on the HPC
      • Atom
      • SSH Mounts
      • Neovim
    • SLURM
    • Modules
    • Gencore Infrastructure
      • Gencore Variant Detection Example
      • Software
        • HPCRunner
        • BioX Workflow
  • ChipSeq analysis
    • CHiP-seq considerations
      • Prerequisites, data summary and availability
    • Deeptools2 bamCoverage
    • Deeptools2 computeMatrix and plotHeatmap using BioSAILs
    • Exercise part4 – Alternative approach in R to plot and visualize the data
  • De novo genome assembly
    • Pre-processing and QC
    • Exercise in de novo assembly
    • Individual Commands
  • Single cell RNA sequencing
    • Prerequisites
    • Seurat part 1 – Loading the data
    • Seurat part 2 – Cell QC
    • Seurat part 3 – Data normalization and PCA
    • Seurat part 4 – Cell clustering
    • Loading your own data in Seurat & Reanalyze a different dataset
  • Metagenomics
    • Quality Control
    • Shotgun Metagenomics
      • Taxonomic Classification
      • Functional Analysis
  • Deep Learning using Keras

BADAS

  • Pheniqs
  • Building R Packages
  • Intro to Nextflow
  • JBrowse: Visualizing Data Quickly & Easily
  • Intro to ggplot
  • Taking it further with ggplot
  • Git and GitHub
  • Seurat: Integration and Label Transfer
  • Nextflow + Containerization
  • Containerization with Docker
  • Jupyter Notebook
  • tidyverse
  • Regular Expressions
  • Customizing Your Unix Environment

Deep Learning using Keras

Slides: https://docs.google.com/presentation/d/1vBo3XJ0sfHTx3S5wzNENsNHY7GC2T5qgI8nTT3ihWm0/edit?usp=sharing

Assignment: https://docs.google.com/document/d/1QSA5o1p87w4cp1ve4gRnUsxc0ZoH9xJc6TNnWmJmpiQ/edit

 

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