Bioinformatics Tutorial
Files Needed
  • Getting Started
    • Setup
    • Run jobs in a Docker
    • Run jobs in a cluster [Advanced]
  • Part I. Programming Skills
    • 1.Linux
      • 1.1.Basic Command
      • 1.2.Practice Guide
      • 1.3.Linux Bash
    • 2.R
      • 2.1.R Basics
      • 2.2.Plot with R
    • 3.Python
  • PART II. BASIC ANALYSES
    • 1.Blast
    • 2.Conservation Analysis
    • 3.Function Analysis
      • 3.1.GO
      • 3.2.KEGG
      • 3.3.GSEA
    • 4.Clinical Analyses
      • 4.1.Survival Analysis
  • Part III. NGS DATA ANALYSES
    • 1.Mapping
      • 1.1 Genome Browser
      • 1.2 bedtools and samtools
    • 2.RNA-seq
      • 2.1.Expression Matrix
      • 2.2.Differential Expression with Cufflinks
      • 2.3.Differential Expression with DEseq2 and edgeR
    • 3.ChIP-seq
    • 4.Motif
      • 4.1.Sequence Motif
      • 4.2.Structure Motif
    • 5.RNA Network
      • 5.1.Co-expression Network
      • 5.2.miRNA Targets
      • 5.3. CLIP-seq (RNA-Protein Interaction)
    • 6.RNA Regulation - I
      • 6.1.Alternative Splicing
      • 6.2.APA (Alternative Polyadenylation)
      • 6.3.Chimeric RNA
      • 6.4.RNA Editing
      • 6.5.SNV/INDEL
    • 7.RNA Regulation - II
      • 7.1.Translation: Ribo-seq
      • 7.2.RNA Structure
    • 8.cfDNA
      • 8.1.Basic cfDNA-seq Analyses
  • Part IV. MACHINE LEARNING
    • 1.Machine Learning Basics
      • 1.1 Data Pre-processing
      • 1.2 Data Visualization & Dimension Reduction
      • 1.3 Feature Extraction and Selection
      • 1.4 Machine Learning Classifiers/Models
      • 1.5 Performance Evaluation
    • 2.Machine Learning with R
    • 3.Machine Learning with Python
  • Part V. Assignments
    • 1.Precision Medicine - exSEEK
      • Help
      • Archive: Version 2018
        • 1.1.Data Introduction
        • 1.2.Requirement
        • 1.3.Helps
    • 2.RNA Regulation - RiboShape
      • 2.0.Programming Tools
      • 2.1.RNA-seq Analysis
      • 2.2.Ribo-seq Analysis
      • 2.3.SHAPE Data Analysis
      • 2.4.Integration
    • 3.RNA Regulation - dsRNA
    • 4.Single Cell Data Analysis
      • Help
  • 5.Model Programming
  • 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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  1. Part III. NGS DATA ANALYSES

7.RNA Regulation - II

Previous6.5.SNV/INDELNext7.1.Translation: Ribo-seq

Last updated 2 years ago

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Features from specific sequencing data

More features can be derived from specific sequencing data for RNA:

Events

Sequencing Methods

Bioinformatics Tools

Ribo-seq

Ribocode, RiboWave, Xtail

icSHAPE, SHAPE-map, DMS-seq

icSHAPE-pipe, shapemapper2

Modification

m6A-seq, MeRIP-seq, miCLIP

m6aViewer, MeRIP-PF

Degradation

Degradome-Seq (PARE-seq)

sPARTA

...

...

...

有些RNA调控事件可以通过于比较特殊的测序方法来测量,例如:

  • 各种RNA修饰(RNA编辑,m6A甲基化等)也会使序列发生改变,进而影响调控因子的结合或导致蛋白序列的改变。常规RNA-seq数据可以用来做RNA编辑的分析,其他的多数RNA修饰需要依赖于特殊的测序方法。

  • miRNA会通过诱导转录本的降解等方式来调控基因表达。有很多生物信息学方法可以用来预测miRNA的结合位点,也有实验方法如Degradome-Seq (PARE-seq)可以通过对被降解的末端进行测序来对miRNA引发的降解事件进行分析。

  • 很多RNA调控的结果是引起翻译的变化。ribo-seq为研究翻译组提供了有力的工具。

  • RNA的结构在RNA调控中发挥了很重要的作用。目前已经有不少测序技术可以用来研究不同条件下细胞内RNA结构的变化,如icSHAPE, SHAPE-map等。

Literatures:

RNA Regulation - Lu Lab Docs
RNA Structure Prediction - Lu Lab Docs
Translation
Structure