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Essential Python For Genome Science
  • Before Start
  • Chapter Contents
  • Prerequisites
    • About the UNIX system
    • About python
  • UNDERSTAND RAW DATA
    • Stages of Genome Data Generation
    • From Bulk To Single Cell
    • Introduction To the Datasets
      • bulk RNA-seq
      • single-cell data
  • Work Environment
    • Chapter Ensemble
    • All About Installations
    • Keep Running
    • Coding Environment
    • Git and Github
    • Other Tips
  • Python and UNIX System
    • Run Python
    • File I/O
    • Run Shell Command In Python - I
    • 🎉Case Study: Mapping bulk RNA-seq reads with salmon
  • Data Cleaning
    • 🎉Key Concept of Pandas
    • 🎉Case Study: Aggregate Salmon Quant
    • Case Study: Exploring The Dataset 🚩
    • The "copy" and "inplace" Parameter 🚩
    • Case Study: Extract and Reformat GTF file 🚩
    • the correct vs. the wrong way of using pandas 🚩
    • Case Study: Bulk Sample PCA 🚩
  • PYTHON BASICS
    • Python can be lightning-fast ⚡️ 🚩
    • Run Shell Command In Python - II 🚩
    • Pointers In Python 🚩
    • Everything is an object 🚩
    • Thread and Process 🚩
    • Resource For Intermediate Python Knowledge 🚩
    • Python magic method 🚩
  • Genome Science Data
    • NGS Data Formats and Tools 🚩
      • SAM/BAM 🚩
      • BED 🚩
      • GTF 🚩
      • Bigwig / Bigbed 🚩
      • VCF / BCF 🚩
    • The Python Packages 🚩
  • Data visualization
    • Matplotlib Basics 🚩
    • Seaborn Basics 🚩
    • Interactive Data Visualization 🚩
  • Use R in Python
    • Why? 🚩
    • rpy2 🚩
  • Gotchas
    • Check whether package X is installed
    • BAM to FASTQ
    • Genomic Websites
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