Showing 30 materials out of 242
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Working with gene and genome annotations
Annotation -
R packages for communicating reproducible research
Workshop -
Bioconductor annotations: using and sharing resources
Annotation -
Liftr & sbgr
Workflows -
Lecture 20-1: Working with Large Data
Big data -
How Bioconductor advances science and contributes to R
Keynote -
The TCGAbiolinks package
Data Integration -
Developing robust and efficient code
Workshop -
Counting reads for RNA-seq in Bioconductor
RNA-Seq -
Bioconductor for Genomic Analysis
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Annotating high throughput data using Bioconductor resources
Annotation -
RNA-Seq 1: differential expression analysis - GLMs and testing
RNA-Seq -
Bioconductor for 'Omics Analysis (University of Rochester Medical Center)
Overview -
Multiple testing
Statistics and probability -
Working with DNA Sequences
Data Representation -
Week 6: Reproducible research with AnVILPublish
Workshop -
Talk
Browsing and searching the Bioconductor codebase
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Lab 9-1: Efficient and Parallel Evaluation
Big data -
Talk
The Bioconductor Project: Current Status
Status -
Introduction to linear models
Statistics and probability -
Lab: Performance and Parallel Evaluation
LargeData -
Introduction to Bioconductor
Bioconductor -
Variants
Variant calling -
DNA-Seq 2: visualisation and quality assessment of variant calls
Sequencing -
Genomic Ranges For Genome-Scale Data And Annotation
Genomics -
Liftr & sbgr
Workflows -
R and Bioconductor for Genomic Analysis
Intro -
Appendix: Install IGV
Appendix -
Best Practices for Managing R / Bioconductor Scripts
Best Practices -
Lab: Plotting Regions from BAM files directly
Variant calling
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