昨晚我們生信技能樹的學(xué)習(xí)大使《二貨潛》神神秘秘的甩給我一個(gè)GitHub資源鏈接,，里面有一份非常好的數(shù)據(jù)分析學(xué)習(xí)資料：加拿大生物信息學(xué)研討會(huì),，而且篤定我們生信技能樹以前沒有分享過,。確實(shí)我在生信技能樹寫了1.3萬(wàn)篇教程,，還真記不清楚我以前有沒有分享過,。但是最近我們就分享過兩個(gè)類似的資源：
學(xué)習(xí)資源真心是比想學(xué)習(xí)的人還多,，不信你就看下去！說實(shí)話,，寫完公眾號(hào),，我看到這個(gè)當(dāng)時(shí)就傻眼了：
文末友情宣傳
強(qiáng)烈建議你推薦給身邊的博士后以及年輕生物學(xué)PI，多一點(diǎn)數(shù)據(jù)認(rèn)知,，讓他們的科研上一個(gè)臺(tái)階：
加拿大生物信息學(xué)研討會(huì)資源寶藏
官方主頁(yè)鏈接：
https:///workshops/2018-epigenomic-data-analysis/
github 鏈接:
https://github.com/bioinformatics-ca
twitter 主頁(yè)：
https://twitter.com/bioinfodotca
各種主頁(yè):
https://bioinformaticsdotca./
youtube 鏈接：
https://www./channel/UCKbkfKk65PZyRCzUwXOJung
最重要：有視頻、有講義 PDF以及PPT ,、有實(shí)戰(zhàn),，并且都是講的特別詳細(xì)。**
**放在最前面的話,，我覺得講義看2019的就行了,。如果加上視頻比較好理解，那就看2018`,。**
容我打開 2019 資料網(wǎng)站：https://bioinformaticsdotca./
點(diǎn)進(jìn)去界面是這樣的：
再往下滑動(dòng)：
好了,，我們可以清楚的看到分為幾大塊。2019
High-throughput Biology: From Sequence to Networks
這部分主要講從序列到最終的調(diào)控網(wǎng)絡(luò),，也包括了一些基礎(chǔ)的 UNIX/R 的學(xué)習(xí),。（這部分 PDF 421 頁(yè)）
準(zhǔn)備工作：
1) R Preparation tutorials:
2) UNIX Preparation tutorials:
3) Sequencing Terminology
4) Cytoscape Preparation tutorials: Complete the introductory tutorial to Cytoscape
培訓(xùn)前需要查看的文獻(xiàn)
Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration
Genome structural variation discovery and genotyping
A survey of sequence alignment algorithms for next-generation sequencing
Genotype and SNP calling from next-generation sequencing data
Informatics for RNA Sequencing: A Web Resource for Analysis on the Cloud
Transcript-level expression analysis of RNA-seq experiments with HISAT, StringTie and Ballgown
ENCODE RNA-Seq Standards
Methods to study splicing from high-throughput RNA sequencing data
A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control Consortium
接下來就是一周的課程安排
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
兩天
Exploratory Analysis of Biological Data Using R
兩天
Bioinformatics for Cancer Genomics
這部分PDF 316 + 49 + 52 頁(yè)
這部分學(xué)癌癥相關(guān)的應(yīng)該是大有用處
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
這部分就是我們最基礎(chǔ)的 RNA-seq 分析所需要做的內(nèi)容 這部分PDF 131 頁(yè)
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
這部分PDF 182 頁(yè)
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
這部分對(duì)于做調(diào)控網(wǎng)絡(luò)的應(yīng)該是大有幫助 這部分PDF 186 頁(yè)
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 年培訓(xùn)資料相關(guān)的。
當(dāng)然這只是一部分,。
文末友情宣傳
強(qiáng)烈建議你推薦給身邊的博士后以及年輕生物學(xué)PI,，多一點(diǎn)數(shù)據(jù)認(rèn)知，讓他們的科研上一個(gè)臺(tái)階：
2018
Informatics on High-Throughput Sequencing Data 2018
課程鏈接：https://bioinformaticsdotca./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
課程鏈接：https://bioinformaticsdotca./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
Day 3
Informatics and Statistics for Metabolomics 2018
課程鏈接：https://bioinformaticsdotca./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
Pathway and Network Analysis of -Omics Data 2018
課程鏈接：https://bioinformaticsdotca./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
Day 3
Introduction to R 2018
課程鏈接：https://bioinformaticsdotca./intror_2018
Exploratory Analysis of Biological Data Using R 2018
課程鏈接：https://bioinformaticsdotca./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
課程鏈接：https://bioinformaticsdotca.//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
Day 4
Day 5
Module 11: Working Reproducibly in the Cloud
Module 12: Big Data Analytics in the Cloud
Module 13: Genes to Pathways
Day 6
Informatics for RNA-Seq Analysis 2018
課程鏈接：https://bioinformaticsdotca./rnaseq_2018
Day 1
Day 2
Day 3
Informatics on High-Throughput Sequencing Data 2018
課程鏈接：https://bioinformaticsdotca./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
課程鏈接：https://bioinformaticsdotca./epigenomics_2018
Day 1
Module 1: Introduction to ChIP Sequencing and Analysis
Module 2: ChIP-Seq Alignment, Peak Calling, and Visualization
Day 2
Analysis of Metagenomic Data 2018
課程鏈接：https://bioinformaticsdotca./metagenomics_2018
Day 1
Day 2
Day 3
Module 6: Metatranscriptomics
Module 7: Statistical Tests for Metagenomics
Module 8: Biomarkers and Bringing It All Together
文末友情宣傳
強(qiáng)烈建議你推薦給身邊的博士后以及年輕生物學(xué)PI,，多一點(diǎn)數(shù)據(jù)認(rèn)知，讓他們的科研上一個(gè)臺(tái)階：
2017
High-Throughput Biology - From Sequence to Networks 2017
課程鏈接：https://bioinformaticsdotca./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
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
Day 6
Infectious Disease Genomic Epidemiology 2017
課程鏈接：https://bioinformaticsdotca./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
Day 3
Bioinformatics of Genomic Medicine 2017
課程鏈接：https://bioinformaticsdotca./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
課程鏈接：https://bioinformaticsdotca./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
Day 3
Introduction to R 2017
課程鏈接：https://bioinformaticsdotca./IntroR_2017
Exploratory Analysis of Biological Data Using R 2017
課程鏈接：https://bioinformaticsdotca./EDA_2017
Day 1
Day 2
Bioinformatics for Cancer Genomics 2017
課程鏈接：https://bioinformaticsdotca.//bicg_2017
Day 1
Day 2
Module 3a: Genome Alignment
Module 3b: Genome Assembly
Module 4: Copy Number Variants
Day 3
Day 4
Day 5
Informatics for RNA-Seq Analysis 2017
課程鏈接：http://bioinformatics-ca./informatics_for_rna_seq_analysis_2016/
Day 1
Day 2
Module 3: Expression and Differential Expression
Module 4: Reference Free Alignment
Module 5: Isoform discovery and alternative expression
Day 3
Informatics on High-Throughput Sequencing Data 2017
課程鏈接：https://bioinformaticsdotca./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
課程鏈接：https://bioinformaticsdotca./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
Epigenomic Data Analysis 2017
課程鏈接：https://bioinformaticsdotca./epigenomics_2017
Day 1
Module 1: Introduction to ChIP Sequencing and Analysis
Module 2: ChIP-Seq Alignment, Peak Calling, and Visualization
Day 2
Microbiome Summer School - Big Data Analytics for Omics Science 2017
課程鏈接：https://bioinformaticsdotca./mss_2017
Day 1
Plenary 1: GUTOME 1010 and Beyond
Plenary 2: Microbiomes, Metagenomes, and Marker Genes
Plenary 3: Metagenomics Analysis
Day 2
Day 3
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
文末友情宣傳
強(qiáng)烈建議你推薦給身邊的博士后以及年輕生物學(xué)PI,，多一點(diǎn)數(shù)據(jù)認(rèn)知,，讓他們的科研上一個(gè)臺(tái)階：
2016
Pathway and Network Analysis of -Omics Data 2016
課程鏈接：http://bioinformatics-ca./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
Day 3
Introduction to R 2016
課程鏈接：http://bioinformatics-ca./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
課程鏈接：http://bioinformatics-ca./exploratory_analysis_of_biological_data_2016/
Day 1
Module 1: Exploratory Data Analysis
Module 2: Regression Analysis
Module 3: Dimension Reduction
Day 2
Bioinformatics for Cancer Genomics 2016
課程鏈接：http://bioinformatics-ca./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
Day 3
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
課程鏈接：http://bioinformatics-ca./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
課程鏈接：http://bioinformatics-ca./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
課程鏈接：http://bioinformatics-ca./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
Epigenomic Data Analysis 2016
課程鏈接：http://bioinformatics-ca./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
Analysis of Metagenomic Data 2016
課程鏈接：http://bioinformatics-ca./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
Day 3
2015
High-Throughput Biology - From Sequence to Networks 2015
課程鏈接：http://bioinformatics-ca./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
Day 4
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
Day 7
Introduction to R 2015
課程鏈接：http://bioinformatics-ca./introduction_to_r_2015/
Day 1
- Module 3: Using R for Data Analysis
Exploratory Analysis of Biological Data Using R 2015
課程鏈接：http://bioinformatics-ca./EDA_in_r_2015/
Day 1
Module 1: Exploratory Data Analysis
Module 2: Regression Analysis
Module 3: Dimension Reduction
Day 2
Bioinformatics for Cancer Genomics 2015
課程鏈接：http://bioinformatics-ca./bioinformatics_for_cancer_genomics_2015/
Day 1
Day 2
Day 3
Day 4
Day 5
Network Analysis using Reactome FI
Pathway and Network Analysis of Omics Data 2015
課程鏈接：http://bioinformatics-ca./pathway_and_network_analysis_2015/
Day 1
Module 1: Introduction to Pathway and Network Analysis
Module 2: Finding over-represented pathways in gene lists
Module 3: Cytoscape Intro, Demo and Enrichment Maps
Day 2
Day 3
Informatics for RNA-Seq Analysis 2015
課程鏈接：http://bioinformatics-ca./rnaseq_analysis_2015/
Day 1
Day 2
Informatics on High-Throughput Data 2015
課程鏈接：http://bioinformatics-ca./high-throughput_sequencing_2015/
Day 1
Module 1: Overview of HT-sequencing & Cloud Computing
Module 2: Reference-guided 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
Informatics and Statistics for Metabolomics 2015
課程鏈接：http://bioinformatics-ca./informatics_and_statistics_for_metabolomics_2015/
Day 1
Module 1: Introduction to Metabolomics
Module 2: Software for Metabolite ID and Quantification
Module 3: Databases for Chemical, Spectral and bIological Data
Day 2
2013 主要是用 R 分析芯片數(shù)據(jù)和流式細(xì)胞數(shù)據(jù)
Microarray Data Analysis
課程鏈接是：
http://bioinformatics-ca./microarrays_2013/
Day 1
Module 1: Introduction to Microarrays and R
Lecture:
Module 1 pdf
Module 1 ppt
Module 1 mp4
Lab Practical:
Modules 1-3 Lab questions
Module 2: Quality Control of Microarrays
Lecture:
Module 2 pdf?
Module 2? ppt
Module 2? mp4
Lab Practical:
Modules 1-3 Lab questions
Day 1 analysis script
Day 2
Module 3: Statistical Analysis
Lecture:
Module 3? pdf
Module 3? ppt
Module 3? mp4
Clustering Slides?
Lab Practical:
Modules 1-3 Lab questions
Status of R script at 11:55am
Status of R script at 12:33pm
Status of R script at 4:24pm
R script with MAS5
Module 4: Beyond the Microarray Experiment
Lecture:
Module 4 pdf
Module 4 ppt
Module 4 mp4
Flow Cytometry Data Analysis using R
課程鏈接是：
http://bioinformatics-ca./flow_cytometry_2013/
Day 1
Module 1: Introduction to Flow Cytometry Analysis in R
Lecture:
Module 1 pdf
Module 1 mp4
Module 2: Exploring FCM data in R
Lecture:
Module 2 pdf?
Module 2? mp4
Lab Practical:
Module 2 Lab
PlottingReference.R - reference, summary and tutorial for plot functions in R.
Module 3: Preprocessing and Quality Assurance of FCM Data
Lecture:
Module 3? pdf
Module 3? mp4
Lab Practical:
Module 3 Lab
Day 2
Module 4: Automated Cell Population Identification
Lecture:
Module 4? pdf
Module 4? mp4
Module 5: 1D Automated Gating
Lecture:
Module 5? pdf
Module 5? mp4
Lab Practical:
Module 5 Lab
Module 6: Additional FCM Tools
Lecture:
Module 6 pdf?
Module 6 mp4
