Bioinformatics Core Competencies

• Calculate DEG gene expression level in the same TAD
• What is JupyterLab?
• Data analysis using Pandas
• Data visualization using Seaborn and many other libraries
• What is MA plot?
• Common NGS data formats and tools
• Hypothesis testing
• Volcano plot
• Find all genes in given TAD region (Language: Chinese)
• DeepTools tutorial
• Gene expression data analysis
• homer motif result interpretation
• Merge ChIP-seq peaks and Diff Gene Tables (Language: Chinese)
• Video tutorial: pooled gRNA screenining
• pysam example: checking softclip reads
• Density plot using python
• Python Heatmap plots

Introduction

It’s always a question about where to start for many people who wants to learn bioinformatics systematically. I think the answer is to make clear about the learning objectives. Bioinformatics people can be generally classified into three categories: Bioinformatics users, Bioinformatics scientists, and Bioinformatics engineers. Here at stjude, most people who want to learn Bioinformatics are actually Bioinformatics users. So our goal is to let them know the following:

• Common Bioinformatics programming languages

• Common Bioinformatics data formats

• Common Bioinformatics data analyses

• Common Bioinformatics tools

• Common Bioinformatics data visualizations

Approach

We are not aiming to provide a systematically Bioinformatics learning course. Rather, we organize our class by topics and for each topic, we provide a self-contained notebook.

Reference

My Ph.D advisor, Dr. Lonnie Welch, contributed significantly to Bioinformatics education, especially on setting up the framework for Bioinformatics Core Competencies. One of the paper I like the most is: [Bioinformatics Curriculum Guidelines: Toward a Definition of Core Competencies](https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003496).

code @ github.