Bioinformatics Tutorial - Basic
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Bioinformatics Tutorial - Basic
Getting Started
Part I. Basic Skills
1.Setup
2.Linux
3.R
4.Python
PART II. BASIC ANALYSES
1.Blast
2.Conservation Analysis
3.Function Analysis
4.Clinical Analyses
Part III. NGS DATA ANALYSES
1.Mapping
2.RNA-seq
3.ChIP-seq
4.Motif
5.Network
5.1.Co-expression Network
5.2.miRNA Targets
5.3. CLIP-seq (RNA-Protein Interaction)
6.RNA Regulation Analyses
Part IV. MACHINE LEARNING
1.Machine Learning Basics
2.Machine Learning with R
3.Machine Learning with Python
Part V. Quiz
1.Precision Medicine - exSEEK
2.RNA Regulation - RiboShape
Appendix
Appendix I. Keep Learning
Appendix II. Databases & Servers
Appendix III. How to Backup
Appendix IV. Teaching Materials
Appendix V. Software and Tools
Appendix VI. Genome Annotations
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5.Network
1) Table of Contents
在
CHIP-seq
一节中,我们介绍了如何通过CHIP-seq数据分析确定特定转录因子和DNA的相互作用关系。本章中我们将介绍更多的推断生物大分子相互关系的生物信息学方法:
5.1.Co-expression Network
: 从表达矩阵出发,判断哪些基因有相似的表达模式
5.2.miRNA Targets
: 从序列出发,用生物信息学工具预测mirna的靶标
5.3.CLIP-seq (RNA-protein interactions)
: 通过CLIP-seq数据分析确定特定RNA结合蛋白(RBP)和RNA的相互作用关系
2) Files Needed
Method 1: Use docker
5.1 Co-expression Network
docker images的下载链接如
附表
所示,下载 bioinfo-coexp.tar.gz 启动新的docker.
# load image tarball
docker
load -i ~/Downloads/bioinfo_coexp.tar.gz
# 请根据下载文件的实际位置调整输入内容
docker
run -dt --name coexpression --restart unless-stopped -v
{
host.machine.shared.directory
}
:/data gangxu/coexpression:1.5
docker
exec
-it coexpression
bash
cd
/home/bioc
5.2 miRNA target prediction
docker
load -i ~/Downloads/bioinfo_mirna_target.tar.gz
docker
run -dt --name mirna --restart unless-stopped -v
{
host.machine.shared.directory
}
:/data mirna_targets:1.0
docker
exec
-it mirna
bash
cd
/home/test/mirna
5.3 CLIP-seq data analysis
Method 2: Directly Download
如果不使用docker,也可以直接从
该链接
中
Files needed by this Tutorial
中的清华云Bioinformatics Tutorial / Files路径下的相应文件夹中下载所需要的文件。
3) Teaching Videos (
link
)
PART III: Network
Previous
4.2.Structure Motif
Next
5.1.Co-expression Network
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Outline
1) Table of Contents
2) Files Needed
Method 1: Use docker
5.1 Co-expression Network
5.2 miRNA target prediction
5.3 CLIP-seq data analysis
Method 2: Directly Download
3) Teaching Videos (link)