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ChIP-seq analysis using R - Experimental design and peak calling.
ChIP-Seq Experimental-design Peak-calling Visualisation
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ChIP-Seq
ChIP-Seq Experimental-design QC ChIP-Seq-QC Data-format Alignment Peak-calling Differential-binding Annotation
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NGS introduction to file formats
HTS-introduction FASTQ BAM VCF WIG CRAM GFF3
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Introduction to NGS and RNA-seq
HTS-introduction Data-format Alignment Differential-expression Feature-summarisation QC
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RNA-Seq Analysis with Biocluster and R
RNA-Seq Alignment Annotation BAM Differential-expression Exploratory-analysis Expression-estimation FASTA FASTQ Feature-summarisation Pre-processing QC Statistical-model
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RNA-Seq
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EMBO High Throughput Sequencing Data Analysis, Cambridge, UK, 2014
RNA-Seq FASTQ GFF3 BAM Populus-tremula Pre-processing QC Alignment Annotation Expression-estimation Differential-expression R-programming
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RNA-seq module Frederik Coppens
HTS-introduction
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Day 1 - RNA-Seq Analysis
Alignment BAM FASTA FASTQ QC
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Material for the course RNA-seq data analysis with Chipster
RNA-Seq FASTQ QC Pre-processing Alignment BAM Expression-estimation Feature-summarisation Differential-expression Statistical-model Exploratory-analysis
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Preprocessing RNA-Seq data
Pre-processing
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ChIP-seq analysis using R - Practical
ChIP-Seq Peak-calling Differential-binding Visualisation Annotation Homo-sapiens R-programming
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Exploratory analysis and downstream analysis
Statistical-model Exploratory-analysis
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Introduction to R and Bioconductor lecture
R-programming
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ChIP-seq analysis using R - Quality Control
RNA-Seq ChIP-Seq QC Data-format Experimental-design
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Guide to R swirl interactive lessons
R-programming
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NGS introduction to sequencing platforms
HTS-introduction
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Nicolas Delhomme - Bastian Schiffthaler - October 2014 EMBO course material
RNA-Seq FASTQ GFF3 BAM Populus-tremula Pre-processing QC Alignment Annotation Expression-estimation Differential-expression R-programming
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Prerequisite
Statistics and probability Unix Linux R-programming Statistics
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RNA-seq module Eija Korpelainen
FASTQ QC Pre-processing Alignment BAM Expression-estimation Feature-summarisation Differential-expression Statistical-model Exploratory-analysis
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Introduction to RNA-seq analysis 2014
Alignment Differential-expression Feature-summarisation Pre-processing QC
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ChIP-seq analysis using R
ChIP-Seq Experimental-design QC Data-format Alignment Peak-calling Differential-binding Visualisation Annotation
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ChIP-seq analysis using R - File formats and QC
RNA-Seq ChIP-Seq QC Data-format Experimental-design
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Example “Variant Calling”
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Day 2 - RNA-Seq Analysis
Alignment BAM FASTA FASTQ QC Exploratory-analysis Feature-summarisation Pre-processing
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Exercises for the course RNA-seq data analysis with Chipster
FASTQ QC Pre-processing Alignment BAM Expression-estimation Feature-summarisation Differential-expression Statistical-model Exploratory-analysis
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Intro to R and Bioconductor
Prerequisite R-programming
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Introduction to R and Bioconductor lecture
R-programming
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Tutorial
RNA-Seq FASTQ GFF3 BAM Populus-tremula Pre-processing QC Alignment Annotation Expression-estimation R-programming
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RNA-seq module Frederik Coppens
FASTQ Alignment BAM Differential-expression Statistical-model Exploratory-analysis
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