Fundamental Skills in Bioinformatics

King Abdullah University of Science and Technology

Fundamental Skills in Bioinformatics

位教师：Jesper Tegner

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4个模块

深入了解一个主题并学习基础知识。

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初级等级

推荐体验

2 周完成

在 10 小时一周

灵活的计划

自行安排学习进度

4个模块

深入了解一个主题并学习基础知识。

92 条评论

初级等级

推荐体验

2 周完成

在 10 小时一周

灵活的计划

自行安排学习进度

您将学到什么

Basics of R
Basics of Python
How to analyze bulk RNAseq count data
How to analyze single cell RNAseq count data

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您将学习的工具

要了解的详细信息

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作业

13 项作业

授课语言：英语（English）

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该课程共有4个模块

The course provides a broad and mainly practical overview of fundamental skills for bioinformatics (and, in general, data analysis). The aim is to support the simultaneous development of quantitative and programming skills for biological and biomedical students with little or no background in programming or quantitative analysis.

The first module will explore the basics of programming through R and this will include: working in R and RStudio, understanding data types, loops and ifs. Additionally, the module will provide an introduction to RMarkDown as a tool for sharing code that we will use in the coding lectures.

涵盖的内容

17个视频2篇阅读材料4个作业

17个视频总计123分钟

Brief introduction to the course2分钟
Lecture: Programming and R4分钟
Lecture: Introduction to RStudio3分钟
Coding Lecture: First contact with RStudio9分钟
Introduction1分钟
Lecture: Data types in R3分钟
Lecture: Data structures in R6分钟
Coding Lecture: Data types in R - atomic and vectors 15分钟
Coding Lecture: Data types in R - lists and matrices17分钟
Coding Lecture: Data types in R - data frames7分钟
Lecture: Introduction to Control Flow4分钟
Lecture: Loops4分钟
Coding Lecture: If statements9分钟
Coding Lecture: loop statements9分钟
Lecture: Loading and Writing6分钟
Coding Lecture: Loading and Writing18分钟
Basics + where to learn more5分钟

2篇阅读材料总计40分钟

Setting up R30分钟
Available data sets to be used in the course.10分钟

4个作业总计95分钟

Introduction to R Quiz20分钟
Data Types in R Quiz15分钟
Control Flow in R Quiz30分钟
Loading and Writing in R Quiz30分钟

The second module will focus on two aims. Firstly, to master the use of logical values and vectors and its applications in quality control. Secondly, to practice the programming skills while learning how to perform basic statistical analysis. This will include: explorative data analysis, correlation, linear models, T-test, and ANOVA. Finally, we will explore the available resources for R programming.

涵盖的内容

20个视频1篇阅读材料2个作业6个编程作业

20个视频总计162分钟

Introduction to Module 21分钟
Lecture: Logical values, logical vectors and operations with them.6分钟
Coding Lecture: Logical Vectors, part 1.11分钟
Coding Lecture: Logical Vectors, part 2.7分钟
Lecture: Data Quality Control.3分钟
Coding Lecture: Quality Control.6分钟
Lecture: Exploratory Data Analysis.8分钟
Coding Lecture: EDA part 1.9分钟
Coding Lecture: EDA part 2.8分钟
Lecture: Correlation12分钟
Coding Lecture: correlation in R6分钟
Lecture: Linear Models8分钟
Coding Lecture: example of a linear model6分钟
Coding Lecture: evaluation of a linear model in R6分钟
Lecture: t-test & ANOVA19分钟
Coding Lecture: t-test.8分钟
Coding Lecture: ANOVA7分钟
Introduction to the dataset: Data set 4.3分钟
Guided analysis.26分钟
Lecture: R packages4分钟

1篇阅读材料总计10分钟

How do R programming assignments work?10分钟

2个作业总计40分钟

Exploratory Data Analysis and Visualization in R30分钟
Programming Assignment Basics Quiz10分钟

6个编程作业总计345分钟

Operating with logical values and matrices180分钟
Quality control of the data 45分钟
Correlation analysis30分钟
Linear models30分钟
t-test and ANOVA30分钟
First analysis of an expression dataset.30分钟

The third module will provide the basics of the Python programming language. First, the module will compare Python and R language and learn the programming syntax of Python. Second, the module will work with two key Python modules: pandas and numpy.

涵盖的内容

19个视频1篇阅读材料4个作业4个编程作业1个非评分实验室

19个视频总计151分钟

Introduction to the module2分钟
Lecture: Python and R2分钟
The Python ecosystem11分钟
Python installation and environments21分钟
Jupyter Lab18分钟
Lecture: Python native data structures2分钟
Coding Lecture: Fundamentals in data types9分钟
Coding Lecture: Lists and Tuples 9分钟
Coding Lecture: Sets and Dictionaries8分钟
Lecture: flow control and functions.1分钟
Coding Lecture: if conditions, for and while loops.17分钟
Coding Lecture: declare and using functions in Python6分钟
Lecture: overview of modules in Python2分钟
Lecture: numpy1分钟
Coding Lecture: numpy10分钟
Lecture: pandas1分钟
Coding Lecture: pandas14分钟
Coding lecture: pandas for data exploration9分钟
Coding Lecture: Visualization9分钟

1篇阅读材料总计3分钟

Free online Python resources3分钟

4个作业总计40分钟

Python primitive values and data structures10分钟
Python syntax: for, if statements and functions10分钟
The numpy package10分钟
The pandas package10分钟

4个编程作业总计120分钟

Python data structures30分钟
Python control flow30分钟
The NumPy package30分钟
The pandas package30分钟

1个非评分实验室总计45分钟

Visualization with the pandas package45分钟

The final module will focus on applying knowledge and understanding of programming in the analysis of real RNA-seq data. R will be used for analysing of bulk RNA-seq and Python for single- cell RNA-seq. The results of both analyses will then be integrated. Finally, the module will provide insights in how to gain deeper knowledge and skills in R.