Bioinformatics Tutorial - Basic
生物信息学实践教程 - 基础篇 (2020版)

Teaching Philosophy

🎦 Study and Practice | 格物致知 知行合一
"Tell me and I forget. Teach me and I remember. Involve me and I learn." - Benjamin Franklin
We teach professional skills in bioinformatics. These skills are not just running software. They will give you the freedom of exploring various real data.

Aim

写在前面的话
相对于过去,突然地,我们发现数据不是太少而是太多,信息不是匮乏而是繁杂,新一代人的重要能力是“鉴别”和“挖掘”。
对生物信息学的工作而言,最重要的、最有用的基本工具和技能过去一直是,我相信很长一段时间也会始终是:
    1.
    google
    2.
    wikipedia
    3.
    知乎
We aim to teach basic data skills that give you freedom.
    Running bioinformatics software isn’t all that difficult, doesn’t take much skill, and it doesn’t embody any of the significant challenges of bioinformatics.…These data skills give you freedom
    I believe these two qualities — reproducibility and robustness.
    So what is a reproducible bioinformatics project? At the very least, it’s sharing your project’s code and data.
    In wet lab biology, when experiments fail, it can be very apparent, but this is not always true in computing. Electrophoresis gels that look like Rorschach blots rather than tidy bands clearly indicate something went wrong. Unfortunately, without prior expectations, it can be quite difficult to distinguish good results from bad results.
    The easy way to ensure everything is working properly is to adopt a cautious attitude , and check everything between computational steps.
    You will almost certainly have to rerun an analysis more than once.
    Write Code for Humans, Write Data for Computers
    Use Existing Libraries Whenever Possible
    Treat Data as Read-Only
    Document Everything (-- Too geeky?) Just as a well-organized laboratory makes a scientist’s life easier, a well-organized and well-documented project makes a bioinformatician’s life easier.
-- <<Bioinformatics Data Skills>>

Major Authors

Yumin Zhu, Gang Xu, Zhuoer Dong, Yinghui Chen, Meifeng Zhou, Xupeng Chen, Xiaocheng Xi, Xi Hu, Jingyi Cao, Xiaofan Liu, Weihao Zhao, Siqi Wang and Zhi J. Lu
Section
Major Authors
Part I. Basic Skills
1.Setup
Zhi John Lu
1.1 Docker
Gang Xu
1.2 Cluster
Gang Xu
2.Linux
Zhi John Lu
2.1 Basic Command
Xi Hu
2.2 Practice Guide
Xi Hu/Zhuoer Dong
2.3 Linux Bash
Gang Xu
3.R
3.1 R Basics
Zhuoer Dong
3.2 Plot with R
Xiaochen Xi/Zhuoer Dong
4.Python
PART II. BASIC ANALYSES
1.Blast
Gang Xu
2.Conservation Analysis
Xi Hu
3.Function Analysis
3.1 GO
Gang Xu
3.2 KEGG
Gang Xu
3.3 GSEA
Zhuoer Dong
Part III. NGS DATA ANALYSES
1.Mapping
Meifeng Zhou/Yumin Zhu
2.RNA-seq
2.1 Differential Expression
Meifeng Zhou
2.2 Alternative Splicing
Zhuoer Dong
3.ChIP-seq
Jingyi Cao
4.Network
4.1.Co-expression Network
Xiaochen Xi
4.2.miRNA Targets
Yumin Zhu
4.3.RBP-RNA Interactions
Yumin Zhu
5.Motif
5.1.Sequence Motif
Yumin Zhu
5.2.Structure Motif
Yumin Zhu
6.RNA Regulation Analyses
6.1.RNA Editing
Yumin Zhu
6.2.APA (Alternative Polyadenylation)
Yumin Zhu
6.3.Ribo-seq
Yumin Zhu
6.4.Structure-seq
Yumin Zhu
6.5.Chimeric RNA
Yinghui Chen
6.6.SNV Calling
Yinghui Chen
7.Clinical Analyses
7.1.ROC Curve
Weihao Zhao/Yumin Zhu
7.2.PCA/tSNE
Xupeng Chen/Xiaofan Liu
7.3.Survival Analysis
Xiaochen Xi/Yumin Zhu
Part IV. MACHINE LEARNING
1.Machine Learning Basics
Xiaofan Liu/Xupeng Chen/Zhi John Lu
2. Machine Learning with R
Xupeng Chen/Xiaofan Liu
3. Machine Learning with Python
Xupeng Chen/Xiaofan Liu
Part V. QUIZ
1.exRNA Biomarker
Xiaofan Liu/Xupeng Chen
2.RNA Regulation
Yizi Zhao
Appendix
Appendix I. Keep Learning
Zhi John Lu
Appendix II. Databases & Servers
Yumin Zhu
Appendix III. How to Backup
Gang Xu/Zhi John Lu
Appendix IV. Teaching Materials
Gang Xu/Xiaofan Liu/Zhi John Lu

Contact Us

Copyright

Copyright © 2021 Lu Lab
2016-2021年于清华园
本书主要目的是用于清华大学《生物信息学导论》本科生课和《生物信息学实践》博士生课的上机指南。
Last modified 1mo ago