Showing 30 materials out of 242
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Counting reads for RNA-seq in Bioconductor
RNA-Seq -
Multiple testing
Statistics and probability -
Working with DNA Sequences
Data Representation -
Lecture 20-1: Working with Large Data
Big data -
Lab 9-1: Efficient and Parallel Evaluation
Big data -
Gene set enrichment - Introduction
Gene-set enrichment analysis -
Talk
Browsing and searching the Bioconductor codebase
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Developing robust and efficient code
Workshop -
RNA-Seq Differential Expression
RNA-Seq -
Talk
R / Bioconductor for open-source analysis and comprehension of high-throughput genomic data
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eQTL analysis -- an approach with Bioconductor
eQTL -
Liftr & sbgr
Workflows -
Genomic Ranges For Genome-Scale Data And Annotation
Genomics -
Lab: Performance and Parallel Evaluation
LargeData -
Week 1: Using R / Bioconductor in AnVIL
Workshop -
Appendix: Install IGV
Appendix -
Bioconductor annotations: using and sharing resources
Annotation -
Gene set enrichment analysis
Gene-set enrichment analysis -
Trends in Genomic Data Analysis in R
R/Bioconductor -
Variants
Variant calling -
eQTL / molecular-QTL analyses
eQTL / molecular-QTL -
Talk
Spatial Transcriptomics Technologies and Analysis Tools
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Week 4: Single-cell RNASeq with 'Orchestrating Single Cell Analysis' in R / Bioconductor
Workshop -
Workshops
Conference -
Experimental design
Experimental design -
Bioconductor
R/Bioconductor -
Talk
Introduction to DataFrames and the impact of recent changes
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05: Bioconductor Annotation Resources
Intro -
Multiple testing
Statistics and probability -
Differential Gene Expression
RNA-Seq
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