加拿大生物信息学研讨会

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今晚我们生信技能树的学习大使《二货潜》神神秘秘的甩给我一个GitHub资源链接，里面有一份非常好的数据分析学习资料：加拿大生物信息学研讨会，而且笃定我们生信技能树以前没有分享过。确实我在生信技能树写了1.3万篇教程，还真记不清楚我以前有没有分享过。但是最近我们就分享过两个类似的资源：

学习资源真心是比想学习的人还多，不信你就看下去！

文末友情宣传

强烈建议你推荐给身边的博士后以及年轻生物学PI，多一点数据认知，让他们的科研上一个台阶：

加拿大生物信息学研讨会资源宝藏

最重要：有视频、有讲义 PDF以及PPT 、有实战，并且都是讲的特别详细。
放在最前面的话，我觉得讲义看 2019 的就行了。如果加上视频比较好理解，那就看 2018。





容我打开 2019 资料网站：https://bioinformaticsdotca.github.io/
点进去界面是这样的：

再往下滑动：

好了，我们可以清楚的看到分为几大块。

2019

High-throughput Biology: From Sequence to Networks

这部分主要讲从序列到最终的调控网络，也包括了一些基础的 UNIX/R 的学习。（这部分 PDF 421 页）

准备工作：

1) R Preparation tutorials:
2) UNIX Preparation tutorials:
3) Sequencing Terminology
4) Cytoscape Preparation tutorials: Complete the introductory tutorial to Cytoscape

培训前需要查看的文献
  • Module 1: Introduction to High-throughput Sequencing
  • Module 2: Data Visualization
  • Module 3: Genome Alignment
  • Module 4: Small-Variant Calling and Annotation
  • Module 5: Structural Variant Calling
  • Module 6: De Novo Assembly
  • Module 7: Introduction to RNA Sequencing Analysis
  • Module 8: RNA-seq Alignment and Visualization
  • Paper: Recurrent chimeric RNAs enriched in human prostate cancer identified by deep sequencing
  • Module 9: Expression and Differential Expression
  • Module 10: Reference Free Alignment
  • Module 11: Isoform Discovery and Alternative Expression
  • Module 12: Introduction to Pathway and Network Analysis
  • Module 13: Finding Over-Represented Pathways
  • Module 14: Network Visualization and Analysis with Cytoscape and Reactome
  • Module 15: More Depth on Network and Pathway Analysis and Cytoscape Enrichment map
  • Module 16: Gene Function Prediction
  • Module 17: Regulatory Network Analysis

    Introduction to R

    两天

    Exploratory Analysis of Biological Data Using R

    两天

    Bioinformatics for Cancer Genomics

    这部分PDF 316 + 49 + 52 页
    这部分学癌症相关的应该是大有用处

  • Module 1: Introduction to Cancer Genomics
  • Module 2: Ethics of Data Usage and Security
  • Module 3: Databases and Visualization Tools
  • Module 4: Genome Alignment
  • Module 5: Genome Assembly-
  • Module 6: Copy Number Variants
  • Module 7: Somatic Mutations and Annotations
  • Module 8: Gene Expression Profiling
  • Module 9: Gene Fusion and Rearrangements
  • Module 10: Genes to Pathways
  • Module 11: Variants to Networks
  • Module 12: Integration of Clinical Data

    Informatics for RNA-Seq Analysis

    这部分就是我们最基础的 RNA-seq 分析所需要做的内容 这部分PDF 131 页

  • Module 1: Introduction to Cloud Computing
  • Module 2: Introduction to RNA Sequencing Analysis
  • Module 3: RNA-seq Alignment and Visualization
  • Module 4: Expression and Differential Expression
  • Module 5: Reference Free Alignment
  • Module 6: Isoform Discovery and Alternative Expression
  • Module 7: Genome Guided and Genome-Free Transcriptome Assembly
  • Module 8: Functional Annotation and Analysis of Transcripts

    Informatics on High-Throughput Sequencing Data

    这部分PDF 182 页

  • Module 1: Introduction to High-throughput Sequencing
  • Module 2: Data Visualization
  • Module 3: Genome Alignment
  • Module 4: Small-Variant Calling and Annotation
  • Module 5: Structural Variant Calling
  • Module 6: De Novo Assembly

    Pathway and Network Analysis of -omics Data

    这部分对于做调控网络的应该是大有帮助 这部分PDF 186 页

  • Module 1: Introduction to Pathway and Network Analysis
  • Module 2 Finding Over-Represented Pathways
  • Module 3: Network Visualization and Analysis with Cytoscape
  • Module 4: More Depth on Network and Pathway Analysis
  • Module 5: Gene Function Prediction
  • Module 6: Regulatory Network Analysis

    Using Clouds for Big Cancer Data Analysis

    上面就是 2019 年培训资料相关的。
    当然这只是一部分。

文末友情宣传

强烈建议你推荐给身边的博士后以及年轻生物学PI，多一点数据认知，让他们的科研上一个台阶：

2018

Informatics on High-Throughput Sequencing Data 2018

课程链接：https://bioinformaticsdotca.github.io/high-throughput_biology_2017

Day 1

  • Module 1: Introduction to High-throughput Sequencing
  • Module 2: Data Visualization
  • Module 3: Genome Alignment

    Day 2

  • Module 4: Small-Variant Calling and Annotation
  • Module 5: Structural Variant Calling
  • Module 6: De Novo Assembly

    Infectious Disease Genomic Epidemiology 2018

    课程链接：https://bioinformaticsdotca.github.io/epidemiology_2018

    Day 1

  • Module 1: Introduction to Public Health Microbiology and Genomic Epidemiology
  • Module 2: Pathogen Genomic Analysis I
  • Module 3: Pathogen Genomic Analysis II

    Day 2

  • Module 4: Antimicrobial Resistance Genes
  • Module 5: Phylogeographic Analysis

    Day 3

  • Module 6: Emerging Pathogen Detection and Identification Using Metagenomics Samples
  • Module 7: Data Visualization

    Informatics and Statistics for Metabolomics 2018

    课程链接：https://bioinformaticsdotca.github.io/metabolomics_2018

    Day 1

  • Module 1: Introduction to Metabolomics
  • Module 2: Metabolite Identification and Annotation
  • Module 3: Databases for Chemical, Spectral, and Biological Data

    Day 2

  • Module 4: Backgrounder in Statistics
  • Module 5: MetaboAnalyst
  • Module 6: Future of Metabolomics

    Pathway and Network Analysis of -Omics Data 2018

    课程链接：https://bioinformaticsdotca.github.io/pathways_2018

    Day 1

  • Module 1: Introduction to Pathway and Network Analysis
  • Module 2: Finding Over-Represented Pathways
  • Module 3: Network Visualization and Analysis with Cytoscape

    Day 2

  • Module 4: More Depth on Pathway and Network Analysis
  • Module 5: Gene Function Prediction

    Day 3

  • Module 6: Regulatory Network Analysis

    Introduction to R 2018

    课程链接：https://bioinformaticsdotca.github.io/intror_2018

    Exploratory Analysis of Biological Data Using R 2018

    课程链接：https://bioinformaticsdotca.github.io/eda_2018

  • Recording Session 1
  • Recording Session 2
  • Recording Session 3
  • Recording Session 4
  • Recording Session 5
  • Recording Session 6
  • Recording Session 7
  • Recording Session 8

    Bioinformatics for Cancer Genomics 2018

    课程链接：https://bioinformaticsdotca.github.io//bicg_2017

    Day 1

  • Module 1: Introduction to cancer genomics
  • Module 2: Databases and Visualization Tools
  • Module 3a: Cancer Databases
  • Module 3b: Visualization Tools

    Day 2

  • Module 4: Genome Alignment
  • Module 5: Genome Assembly
  • Module 6: Copy Number Variants

    Day 3

  • Module 7: Somatic Mutations and Annotations
  • Module 8: Gene Expression

    Day 4

  • Module 9: Gene Fusion and Rearrangements
  • Module 10: Sharing and Scaling a VM

    Day 5

  • Module 11: Working Reproducibly in the Cloud
  • Module 12: Big Data Analytics in the Cloud
  • Module 13: Genes to Pathways

    Day 6

  • Module 14: Variants to Networks
  • Module 15: Clinical Data Integration

    Informatics for RNA-Seq Analysis 2018

    课程链接：https://bioinformaticsdotca.github.io/rnaseq_2018

    Day 1

  • Module 1: Introduction to RNA Sequencing and Analysis
  • Module 2: RNA-seq alignment and visualization

    Day 2

  • Module 3: Expression and Differential Expression
  • Module 4: Reference Free Alignment

    Day 3

  • Module 5: Genome-Free De Novo Transcriptome Assembly
  • Module 6: Functional Annotation and Analysis of Transcripts

    Informatics on High-Throughput Sequencing Data 2018

    课程链接：https://bioinformaticsdotca.github.io/htseq_2018

    Day 1

  • Module 1: Introduction to High-throughput Sequencing
  • Module 2: Data Visualization
  • Module 3: Genome Alignment

    Day 2

  • Module 4: Small-Variant Calling and Annotation
  • Module 5: Structural Variant Calling
  • Module 6: De Novo Assembly

    Epigenomic Data Analysis 2018

    课程链接：https://bioinformaticsdotca.github.io/epigenomics_2018

    Day 1

  • Module 1: Introduction to ChIP Sequencing and Analysis
  • Module 2: ChIP-Seq Alignment, Peak Calling, and Visualization

    Day 2

  • Module 3: Introduction to WGBS and Analysis
  • Module 4: Downstream Analyses and Integrative Tools

    Analysis of Metagenomic Data 2018

    课程链接：https://bioinformaticsdotca.github.io/metagenomics_2018

    Day 1

  • Module 1: Introduction to Metagenomics
  • Module 2: Marker Gene-Based Analysis
  • Module 3: PICRUSt

    Day 2

  • Module 4: Metagenomic Taxanomic and Functional Composition
  • Module 5: Pulling Genomes from Metagenomes

    Day 3

  • Module 6: Metatranscriptomics
  • Module 7: Statistical Tests for Metagenomics
  • Module 8: Biomarkers and Bringing It All Together

文末友情宣传

强烈建议你推荐给身边的博士后以及年轻生物学PI，多一点数据认知，让他们的科研上一个台阶：

2017

High-Throughput Biology - From Sequence to Networks 2017

课程链接：https://bioinformaticsdotca.github.io/high-throughput_biology_2017

Day 1

  • Module 1: Introduction to High-throughput Sequencing
  • Module 2: Data Visualization
  • Module 3: Genome Alignment

    Day 2

  • Module 4: Small-Variant Calling and Annotation
  • Module 5: Structural Variant Calling
  • Module 6: De Novo Assembly

    Day 3

  • Module 7: Introduction to RNA Sequencing Analysis
  • Module 8: RNA-seq Alignment and Visualization

    Day 4

  • Module 9: Expression and Differential Expression
  • Module 10: Reference Free Alignment
  • Module 11: Isoform Discovery and Alternative Expression

    Day 5

  • Module 12: Introduction to Pathway and Network Analysis
  • Module 13: Finding Over-Represented Pathways
  • Module 14: Network Visualization and Analysis with Cytoscape

    Day 6

  • Module 15: More Depth on Network and Pathway Analysis
  • Module 16: Gene Function Prediction

    Day 6

  • Module 17: Regulatory Network Analysis

    Infectious Disease Genomic Epidemiology 2017

    课程链接：https://bioinformaticsdotca.github.io/genomic_epidemiology_2017

    Day 1

  • Module 1: Introduction to Public Health Microbiology and Genomic Epidemiology
  • Module 2: Pathogen Genomic Analysis I
  • Module 3: Pathogen Genomic Analysis II

    Day 2

  • Module 4: Antimicrobial Resistance Genes
  • Module 5: Phylogeographic Analysis

    Day 3

  • Module 6: Emerging Pathogen Detection and Identification Using Metagenomics Samples
  • Module 7: Data Visualization

    Bioinformatics of Genomic Medicine 2017

    课程链接：https://bioinformaticsdotca.github.io/genomic_medicine_2017

    Day 1

  • Module 1: Introduction and Patient Phenotyping and Genetic Disease
  • Module 2: Introduction to Tools, Computing Infrastructure, and Data
  • Module 3: Variant Annotation
  • Module 4: Translating Research Workflows into Clinical Tests

    Day 2

  • Module 5: Available Epigenetics Data and Resources
  • Module 6: Epigenetic Profiling in Disease
  • Module 7: Patient Similarity Fusion

    Pathway and Network Analysis of -Omics Data 2017

    课程链接：https://bioinformaticsdotca.github.io/pathways_2017

    Day 1

  • Module 1: Introduction to Pathway and Network Analysis
  • Module 2: Finding Over-Represented Pathways in Gene Lists
  • Module 3: Network Visualization and Analysis with Cytoscape

    Day 2

  • Module 4: More Depth on Pathway and Network Analysis
  • Module 5: Gene Function Prediction

    Day 3

  • Module 6: Regulatory Network Analysis

    Introduction to R 2017

    课程链接：https://bioinformaticsdotca.github.io/IntroR_2017

    Exploratory Analysis of Biological Data Using R 2017

    课程链接：https://bioinformaticsdotca.github.io/EDA_2017

    Day 1

  • Module 1: Exploratory Data Analysis
  • Module 2: Regression
  • Module 3: Dimension Reduction

    Day 2

  • Module 4: Clustering
  • Module 5: Hypothesis Testing

    Bioinformatics for Cancer Genomics 2017

    课程链接：https://bioinformaticsdotca.github.io//bicg_2017

    Day 1

  • Module 1: Introduction to cancer genomics
  • Module 2: Databases and Visualization Tools

    Day 2

  • Module 3a: Genome Alignment
  • Module 3b: Genome Assembly
  • Module 4: Copy Number Variants

    Day 3

  • Module 5: Somatic Mutations and Annotations
  • Module 6: Gene Expression

    Day 4

  • Module 7: Gene Fusion and Rearrangements
  • Module 8: Variants to Networks

    Day 5

  • Module 8: Variants to Networks
  • Module 9: Clinical Data Integration

    Informatics for RNA-Seq Analysis 2017

    课程链接：http://bioinformatics-ca.github.io/informatics_for_rna_seq_analysis_2016/

    Day 1

  • Module 1: Introduction to RNA Sequencing and Analysis
  • Module 2: RNA-seq alignment and visualization

    Day 2

  • Module 3: Expression and Differential Expression
  • Module 4: Reference Free Alignment
  • Module 5: Isoform discovery and alternative expression

    Day 3

  • Module 6: Genome-Free De Novo Transcriptome Assembly
  • Module 7: Functional Annotation and Analysis of Transcripts

    Informatics on High-Throughput Sequencing Data 2017

    课程链接：https://bioinformaticsdotca.github.io/htseq_2017

    Day 1

  • Module 1: Introduction to High-throughput Sequencing
  • Module 2: Data Visualization
  • Module 3: Genome Alignment

    Day 2

  • Module 4: Small-Variant Calling and Annotation
  • Module 5: Structural Variant Calling
  • Module 6: De Novo Assembly

    Informatics and Statistics for Metabolomics 2017

    课程链接：https://bioinformaticsdotca.github.io/metabolomics_2017

    Day 1

  • Module 1: Introduction to Metabolomics
  • Module 2: Metabolite Identification and Annotation
  • Module 3: Databases for Chemical, Spectral, and Biological Data

    Day 2

  • Module 4: Backgrounder in Statisticss
  • Module 5: MetaboAnalyst
  • Module 6: Future of Metabolomics

    Epigenomic Data Analysis 2017

    课程链接：https://bioinformaticsdotca.github.io/epigenomics_2017

    Day 1

  • Module 1: Introduction to ChIP Sequencing and Analysis
  • Module 2: ChIP-Seq Alignment, Peak Calling, and Visualization

    Day 2

  • Module 3: Introduction to WGBS and Analysis
  • Module 4: Downstream Analyses and Integrative Tools

    Microbiome Summer School - Big Data Analytics for Omics Science 2017

    课程链接：https://bioinformaticsdotca.github.io/mss_2017

    Day 1

  • Plenary 1: GUTOME 1010 and Beyond
  • Plenary 2: Microbiomes, Metagenomes, and Marker Genes
  • Plenary 3: Metagenomics Analysis

    Day 2

  • Plenary 4: Microbiome Biomarker Discovery
  • Plenary 5: Metatranscriptomics

    Day 3

  • Plenary 6: Host Genomics Applied to the Microbiome
  • Plenary 7: Introduction to Machine Learning for Biological Data

    Day 4

  • Plenary 8: ElasticSearch to Facilitate Data Mining of Human Microbiome Databases
  • Plenary 9: Algorithms for Mass Spectrometry
  • Plenary 10: Efficient Multi-Locus Biomarker Discovery

文末友情宣传

强烈建议你推荐给身边的博士后以及年轻生物学PI，多一点数据认知，让他们的科研上一个台阶：

2016

Pathway and Network Analysis of -Omics Data 2016

课程链接：http://bioinformatics-ca.github.io/pathway_and_network_analysis_of_omics_data_2016/

Day 1

  • Module 1: Introduction to Pathway and Network Analysis
  • Module 2: Finding Over-Represented Pathways in Gene Lists
  • Module 3: Network Visualization and Analysis with Cytoscape

    Day 2

  • Module 4: More Depth on Pathway and Network Analysis
  • Module 5: Gene Function Prediction

    Day 3

  • Module 6: Regulatory Network Analysis

    Introduction to R 2016

    课程链接：http://bioinformatics-ca.github.io/introduction_to_r_2016/

    Day 1

  • Module 1: The R Environment
  • Module 2: Programming Basics
  • Module 3: Using R for Data Analysis

    Exploratory Analysis of Biological Data Using R 2016

    课程链接：http://bioinformatics-ca.github.io/exploratory_analysis_of_biological_data_2016/

    Day 1

  • Module 1: Exploratory Data Analysis
  • Module 2: Regression Analysis
  • Module 3: Dimension Reduction

    Day 2

  • Module 4: Clustering Analysis
  • Module 5: Hypothesis Testing for EDA

    Bioinformatics for Cancer Genomics 2016

    课程链接：http://bioinformatics-ca.github.io/bioinformatics_for_cancer_genomics_2016/

    Day 1

  • Module 1: Introduction to cancer genomics
  • Module 2.1: Databases and Visualization Tools
  • Module 2.2: Logging into the Cloud

    Day 2

  • Module 3: Mapping and Genome Rearrangement
  • Module 4: Gene Fusion Discovery

    Day 3

  • Module 5: Copy Number Alterations
  • Module 6: Somatic Mutations

    Day 4

  • Module 7: Gene Expression Profiling
  • Module 8: Variants to Pathways
  • Part 1: How to annotate variants and prioritize potentially relevant ones
  • Part 2: From genes to pathways

    Day 5

    Network Analysis using Reactome

    Informatics for RNA-Seq Analysis 2016

    课程链接：http://bioinformatics-ca.github.io/informatics_for_rna_seq_analysis_2016/

    Day 1

  • Module 0: Introduction to Cloud Computing
  • Module 1: Introduction to RNA Sequencing and Analysis
  • Module 2: RNA-seq alignment and visualization

    Day 2

  • Module 3: Expression and Differential Expression
  • Module 4: Isoform discovery and alternative expression
  • Module 5: Reference Free Alignment

    Informatics on High-Throughput Sequencing Data 2016

    课程链接：http://bioinformatics-ca.github.io/informatics_on_high-throughput_sequencing_data_2016/

    Day 1

  • Module 1: Introduction to HT-sequencing and Cloud Computing
  • Module 2: Genome Alignment
  • Module 3: Genome Visualization
  • Module 4: De Novo Assembly

    Day 2

  • Module 5: Genome Variation
  • Module 6: Genome Structural Variation
  • Module 7: Bringing it Together with Galaxy

    Informatics and Statistics for Metabolomics 2016

    课程链接：http://bioinformatics-ca.github.io/informatics_and_statistics_for_metabolomics_2016/

    Day 1

  • Module 1: Introduction to Metabolomics
  • Module 2: Metabolite Identification and Annotation
  • Module 3: Databases for Chemical, Spectral, and Biological Data

    Day 2

  • Module 4: Backgrounder in Statistical Methods
  • Module 5: MetaboAnalyst
  • Module 6: Future of Metabolomics

    Epigenomic Data Analysis 2016

    课程链接：http://bioinformatics-ca.github.io/epigenomic_data_analysis_2016/

    Day 1

  • Module 1: Introduction to ChIP Sequencing and Analysis
  • Module 2: ChIP-Seq Alignment, Peak Calling, and Visualization

    Day 2

  • Module 3: Introduction to WGBS and Analysis
  • Module 4: Downstream Analyses and Integrative Tools

    Analysis of Metagenomic Data 2016

    课程链接：http://bioinformatics-ca.github.io/analysis_of_metagenomic_data_2016/

    Day 1

  • Module 1: Introduction to Metagenomics and Computing in the Cloud
  • Module 2: Marker Gene-based Analysis of Taxonomic Composition
  • Module 3: Introduction to PICRUSt

    Day 2

  • Module 4: Metagenomic Taxonomic Composition
  • Module 5: Metagenomic Functional Composition

    Day 3

  • Module 6: Metatranscriptomics
  • Module 7: Biomarker Selection

    2015

    High-Throughput Biology - From Sequence to Networks 2015

    课程链接：http://bioinformatics-ca.github.io/high_throughput_biology_2015/

    Day 1

  • Module 1: Overview of HT-sequencing & Cloud Computing
  • Module 2: Reference Genome Alignment
  • Module 3: Data Visualization
  • Module 4: De Novo Assembly

    Day 2

  • Module 5: Small variant calling & annotation
  • Module 6: Structural variation calling
  • Module 7: Bringing it all Together: Galaxy

    Day 3

  • Module 8: Introduction to RNA sequencing and analysis
  • Module 9: RNA-seq alignment and visualization

    Day 4

  • Module 10: Expression and Differential Expression
  • Module 11: Isoform discovery and alternative expression

    Day 5

  • Module 12: Introduction to Pathway and Network Analysis
  • Module 13: Finding over-represented pathways in gene lists
  • Module 14: Cytoscape Intro, Demo and Enrichment Maps

    Day 6

  • Module 15: Depth on Pathway and Network Analysis
  • Module 16: Gene Function Prediction

    Day 7

  • Module 17: Gene Regulation Network Analysis

    Introduction to R 2015

    课程链接：http://bioinformatics-ca.github.io/introduction_to_r_2015/

    Day 1

  • Module 1: First Steps
  • Module 2: Programming Basics
  • Module 3: Using R for Data Analysis

Exploratory Analysis of Biological Data Using R 2015

课程链接：http://bioinformatics-ca.github.io/EDA_in_r_2015/

Day 1

文末友情宣传

强烈建议你推荐给身边的博士后以及年轻生物学PI，多一点数据认知，让他们的科研上一个台阶：

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