Bioinformatics Tutorial
《生物信息学实践教程》
Last updated
《生物信息学实践教程》
Last updated
🎦 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.
本书主要用于清华大学本科生课《生物信息学》和博士生课《生物信息学实践》
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:
wikipedia
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>>
基本生物课程: 如《遗传学》和/或《分子生物学》
基本统计课程: 如《概率论》和/或《生物统计》
基本数学课程: 如《微积分》和《线性代数》
基本计算机课程:如 《Linux》和《C或Python语言》
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/Yunfan Jin |
1.2 Cluster | Gang Xu/Xiaofan Liu/Yunfan Jin |
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 | Yuhuan Tao |
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 |
4.Clinical Analysis | |
4.1 Survival Analysis | Xiaochen Xi/Yumin Zhu |
Part III. NGS DATA ANALYSES | |
1.Mapping | Meifeng Zhou/Yumin Zhu |
1.1 Genome Browser | Xiaofan Liu/Shang Zhang |
1.2 bedtools and samtools | Xiaofan Liu/Yunfan Jin |
2.RNA-seq | |
2.1 Expression Matrix | Xiaofan Liu |
2.2 Differential Expression with Cufflinks | Meifeng Zhou/Shang Zhang |
2.3 Differential Expression with DEseq2 and edgeR | Xinzhe Ni/Shang Zhang |
2.4 Alternative Splicing | Zhuoer Dong/Shang Zhang |
3.ChIP-seq | Jingyi Cao/Xiaofan Liu |
4.Motif | |
4.1 Sequence Motif | Yumin Zhu |
4.2 Structure Motif | Yumin Zhu |
5.Network | |
5.1 Co-expression Network | Xiaochen Xi |
5.2 miRNA Targets | Yumin Zhu |
5.3 CLIP-seq(RNA-Protein Interactions) | Yumin Zhu/Xiaofan Liu |
6.RNA Regulation Analyses | |
6.1 Alternative Splicing | Zhuoer Dong/Shang Zhang |
6.2 APA (Alternative Polyadenylation) | Yumin Zhu |
6.3 Chimeric RNA | Yinghui Chen |
6.4 RNA Editing | Yumin Zhu |
6.5 SNV/INDEL | Yinghui Chen |
6.6 RNA Modification | |
6.7 RNA Degradation | |
6.8 Translation:Ribo-seq | Yumin Zhu/Weihao Zhao/Xiaofan Liu |
6.9 RNA Structure | Yumin Zhu/Xiaofan Liu |
Part IV. MACHINE LEARNING | |
1.Machine Learning Basics | Xiaofan Liu/Xupeng Chen/Zhi John Lu |
1.1 Data Pre-processing | Xinzhe Ni/Xiaofan Liu |
1.2 Data Visualization & Dimension Reduction | Xinzhe Ni/Xiaofan Liu |
1.3 Feature Extraction and Selection | Xinzhe Ni/Xiaofan Liu |
1.4 Machine Learning Classifiers/Models | Xinzhe Ni/Xiaofan Liu |
1.5 Performance Evaluation | Xiaofan Liu |
2.Machine Learning with R | Xupeng Chen/Xiaofan Liu |
3.Machine Learning with Python | Xupeng Chen/Xiaofan Liu |
Part V. QUIZ | |
1.Precision Medicine - exSEEK | Xiaofan Liu/Xupeng Chen |
2.RNA Regulation - RiboShape | Xiaofan Liu/Yizi Zhao |
3.Single Cell Data Analysis | Yu Li |
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 |
Appendix V. Software and Tools | Yumin Zhu |
Lu Lab 鲁 志 实验室
School of Life Sciences, Tsinghua University, Beijing, China
e-mail: lulab1 AT tsinghua.edu.cn
Homepage: www.ncRNAlab.org ( lulab.life.tsinghua.edu.cn )
Software: software.ncRNAlab.org
Courses: courses.ncRNAlab.org
Books: book.ncRNAlab.org ( bioinfo.gitbook.io )
Docs: docs.ncRNAlab.org ( lulab.gitbook.io | lulab.github.io )
Copyright © 2024 Lu Lab
https://www.apache.org/licenses/LICENSE-2.0
2016-2024年于清华园