前些天我在生信技能树重新唤起来了大家的记忆：都不知道自己还有一本生物信息学的书 ，因为是中文的接地气的教程合辑，所以受大家喜爱，我已经在出版社的鞭策下努力让他早日现世，这样大家以后带师弟师妹的时候也方便推荐教材。

这里还是推荐另外一个类似的教程，跟我们的目录都差不多，挺好的，可以互相对应着看，查漏补缺。他们的网页里面不仅仅是这本书，还有很多一直在更新的博客教程，类似于我们生信技能树公众号一样：

https://gencore.bio.nyu.edu/bioinformatics/ 感兴趣的朋友甚至可以收藏起来，避免下次找不到这么好的资源了。

This e-book contains resources for mastering NGS analysis. It has been generated by the Bioinformatics team at NYU Center For Genomics and Systems Biology in New York and Abu Dhabi.

TOPICS

• Next-Generation Sequencing Analysis Resources
• Introduction to Linux
  • Linux Exercise
  • Nano Tutorials
• Pre-Requisites
• NGS Sequencing Technology and File Formats
  • How Sequencing Works
  • FastA Format
  • FastQ Format
  • Quality Scores
  • SAM/BAM/CRAM Format
  • BED Format
  • VCF Format
  • GFF3 Format
• Alignment
  • Trimming with Trimmomatic
• Visualization
• Variant Calling
  • Pre-Processing
  • Variant Discovery
• RNA-seq Analysis
  • Aligning RNA-seq data
  • Introduction to R
  • DESeq
  • DESeq 2
  • Gene Set Enrichment Analysis with ClusterProfiler
  • Over-Representation Analysis with ClusterProfiler
  • Salmon & kallisto: Rapid Transcript Quantification for RNA-Seq Data
  • Instructions to install R Modules on Dalma
• HPC
  • Resources for editing files on the HPC
  • Atom
  • SSH Mounts
  • Neovim
  • SLURM
  • Modules
  • Gencore Infrastructure
  • Gencore Variant Detection Example
  • Software
  • HPCRunner
  • BioX Workflow
• ChipSeq analysis
  • CHiP-seq considerations
  • Prerequisites, data summary and availability
  • Deeptools2 bamCoverage
  • Deeptools2 computeMatrix and plotHeatmap using BioSAILs
  • Exercise part4 – Alternative approach in R to plot and visualize the data
• De novo genome assembly
  • Pre-processing and QC
  • Exercise in de novo assembly
  • Individual Commands
• Single cell RNA sequencing
  • Prerequisites
  • Seurat part 1 – Loading the data
  • Seurat part 2 – Cell QC
  • Seurat part 3 – Data normalization and PCA
  • Seurat part 4 – Cell clustering
  • Loading your own data in Seurat & Reanalyze a different dataset
• Metagenomics
  • Quality Control
  • Shotgun Metagenomics
  • Taxonomic Classification
  • Functional Analysis
• Deep Learning using Keras