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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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  • Author
  • Why python?
  • What do I want to write?
  • The Intermediate Level
  • About me

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Before Start

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Last updated 5 years ago

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Author

Hanqing Liu (刘翰青)

Why python?

What do I want to write?

My experience on using python in genome science, with a focus on intermediate level python programming, and some basic introduction to genome science.

The Intermediate Level

About me

I like learning new things, especially things that looks beautiful. Learning python is the best choice I made during my time at college. And it become more and more useful in my daily research.

For the current research, I study brain methylome at single-cell level. I didn't learn anything about neuroscience at college, but I'm really fascinated by it now. I will continue my journey on neuroscience after getting my Ph.D., no matter what aspect of it.

For enjoying life, photography! But sadly, not during this coronavirus pandemic.

Here are some links about me:

Python is simple and versatile. It's a than R (the other language that's mainly used by bioinformatician and statistician). Yet , its not hard to . For other daily works, I choose python over R.

Above is my favorite joke about learning programming. But I guess its also right for learning anything, especially for self-learning on anything. are always available, especially for hot words like "python" or "genomics". Advanced level materials are usually domain-specific, and people who study that, know how to get the information. The intermediate level means the massive gap between understanding the "introduction to X" and becoming an expert. And here I want to write about my experience of passing this level. Having that said, I only consider myself at the "late-stage" of intermediate level, not a wholly expert. But I guess the "fresh experience" can sometimes be more useful than pure knowledge, just like .

I am writing in parallel.

much more popular programming language
R is still useful in many aspect
integrate some open-box R packages into python
Introduction level materials
one of my favorite books about the learning experience
Github
Google Scholar
My Lab
A more technical book
https://xkcd.com/353/
How to draw an Owl
5-min walk to my office at the Salk Institute