加拿大生物信息学研讨会资源宝藏

生信技能树

发布于 2020-03-05 09:42:35

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发布于 2020-03-05 09:42:35

昨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！说实话，写完公众号，我看到这个当时就傻眼了：

加拿大生物信息学研讨会资源宝藏

官方主页链接： https://bioinformatics.ca/workshops/2018-epigenomic-data-analysis/
github 链接: https://github.com/bioinformatics-ca
twitter 主页： https://twitter.com/bioinfodotca
各种主页: https://bioinformaticsdotca.github.io/
youtube 链接： https://www.youtube.com/channel/UCKbkfKk65PZyRCzUwXOJung

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

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

接下来就是一周的课程安排

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

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。

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

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

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

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 2015

课程链接：http://bioinformatics-ca.github.io/bioinformatics_for_cancer_genomics_2015/

Day 1

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

Day 2

Module 3: Alignment and Genome rearrangements
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

Day 5

Network Analysis using Reactome FI

Pathway and Network Analysis of Omics Data 2015

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

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

Day 3

Module 6: Gene Regulation Network Analysis

Informatics for RNA-Seq Analysis 2015

课程链接：http://bioinformatics-ca.github.io/rnaseq_analysis_2015/

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: Isoform discovery and alternative expression

Informatics on High-Throughput Data 2015

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

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

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

2013 主要是用 R 分析芯片数据和流式细胞数据

Microarray Data Analysis

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

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

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