Courses & Conferences
Bioconductor provides training in computational and statistical methods for the analysis of genomic data. You are welcome to use material from previous courses. However, you may not include these in separately published works (articles, books, websites). When using all or parts of the Bioconductor course materials (slides, vignettes, scripts) please cite the authors and refer your audience to the Bioconductor website.
Upcoming events are advertised 6 to 8 weeks in advance.
| Keyword | Title | Course | Materials | Date | Bioc/R Version |
|---|---|---|---|---|---|
| Intro / RNA-seq | R and Bioconductor for Genomic Analysis, Martin Morgan | OSU | Using R html, Rmd; Data Input and Manipulation html, Rmd; Statistics and Graphics html, Rmd; Introduction to Bioconductor html, Rmd; Bioconductor Building Blocks html, Rmd; An RNA-seq Work Flow html, Rmd; Appendix: Quantifying Gene Expression Using salmon html, Rmd | 2017‑09‑11 | 3.6/3.4 |
| Conference | BioC2017: Where Software and Biology Connect, Various authors | BioC2017 | Course material | 2017‑07‑26 | 3.6/3.4 |
| Packages | Introduction to new package development and submission, Lori Shepherd | BioC2017 | Make A Package: html, Github | 2017‑07‑26 | 3.6/3.4 |
| Cloud | Cloud and other creative approaches to working with big data, Vincent Carey, Sean Davis | BioC2017 | Workshop Github | 2017‑07‑26 | 3.6/3.4 |
| Git | Git with the program: new Bioconductor version control, Nitesh Turaga | BioC2017 | pdf slides | 2017‑07‑26 | 3.6/3.4 |
| Best Practices | Developer best practices, Martin Morgan, Kasper Hansen | BioC2017 | Unit tests, Efficiency, Query Web Resource, Coding Style, Common Bioconductor Classes and Import | 2017‑07‑26 | 3.6/3.4 |
| Large Data | Working with large arrays: the DelayedArray package, Hervé Pagès | BioC2017 | Working with large arrays: pdf slides, R, Rnw | 2017‑07‑26 | 3.6/3.4 |
| Introduction | Introduction to R and Bioconductor, Lori Shepherd | BioC2017 | Intro course: Github | 2017‑07‑26 | 3.6/3.4 |
| Genomic Ranges | A Journey of Discovery through the GenomicRanges Infrastructure, Michael Lawrence | BioC2017 | pdf slides, R, Github | 2017‑07‑26 | 3.6/3.4 |
| Microbiome | Microbiome Data Analysis, Levi Waldron, Susan Holmes, Pau J. McMurdie, Edoardo Pasolli, Joe Paulson, Lucas Schiffer, Justin Wagner | BioC2017 | MicrobiomeWorkshop: html, R, Rmd MicrobiomeWorkshop II: html, R, Rmd Github |
2017‑07‑26 | 3.6/3.4 |
| RNA | Design and evaluate guide RNAs for CRISPR-Cas9 genome-editing using CRISPRseek and GUIDEseq, Lihua Julie Zhu | BioC2017 | pdf slides, Github CRISPRdemo: html, R, Rmd GUIDEseqdemo: html, R, Rmd |
2017‑07‑26 | 3.6/3.4 |
| Workflows | Differential Gene Expression analysis using R and Bioconductor, Radhika Khetani, Meeta Mistry, Mary Piper | BioC2017 | Workflow | 2017‑07‑26 | 3.6/3.4 |
| Visualization | Interactive visualization and data analysis with epiviz web components, Jayaram Kancherla, Hector Corrada Bravo, Brian Gottfried | BioC2017 | data preprocessing: html, R, Rmd minfi: html, R, Rmd Bioc2017 Addendum: html, R, Rmd Github |
2017‑07‑26 | 3.6/3.4 |
| Enrichment | Functional enrichment analysis of high-throughput omics data in Bioconductor, Ludwig Geistlinger, Levi Waldron | BioC2017 | pdf slides, Github enrichOmics: html, R, Rmd |
2017‑07‑26 | 3.6/3.4 |
| RNAseq | Learn to leverage 70,000 human RNA-seq samples for your projects, Leonardo Collado Torres | BioC2017 | pdf slides, Github recount workshop: html, R, Rmd |
2017‑07‑26 | 3.6/3.4 |
| Enrichment | Ensembl gene set enrichment analysis with EGSEA, Matt Ritchie | BioC2017 | EGSEA workflow: html, R, Rmd Github |
2017‑07‑26 | 3.6/3.4 |
| Single-cell | Bioconductor workflow for single-cell RNA-seq data analysis: dimensionality reduction, clustering, and pseudotime ordering, Fanny Perraudeau, Kelly Street, Davide Risso, Sandrine Dudoit, Elizabeth Purdom | BioC2017 | pdf slides, Github Workshop: html, R, Rmd |
2017‑07‑26 | 3.6/3.4 |
| Introduction | Integrative analysis workshop with TCGAbiolinks and ELMER, Tiago Chedraoui Silva, Houtan Noushmehr, Benjamin Berman | BioC2017 | Analysis: html, R, Rmd AnalysisGui: html, R, Rmd Data: html, R, Rmd DataGui: html, R, Rmd Github, Workshop Link |
2017‑07‑26 | 3.6/3.4 |
| Workflows | CyTOF workflow: differential discovery in high-throughput high-dimensional cytometry datasets, Malgorzata Nowicka, Lukas M. Weber, Mark D. Robinson | BioC2017 | Workshop: html, Rmd pdf Slides, Github, Workflow |
2017‑07‑26 | 3.6/3.4 |
| Annotation | Understanding Bioconductor Annotation Packages, James MacDonald | BioC2017 | Workshop: html, R, Rmd Github |
2017‑07‑26 | 3.6/3.4 |
| Annotation | Variant Annotation Workshop with FunciVAR, StateHub, and MotifBreakR, Dennis J. Hazelett, Simon G Coetzee | BioC2017 | Workshop Link: html | 2017‑07‑26 | 3.6/3.4 |
| ChIP-seq | Integrative analysis and visualization of ChIP-seq data using ChIPpeakAnno , GeneNetworkBuilder, and TrackViewer, Jianhong Ou, Lihua Julia Zhu, Jun Yu | BioC2017 | pdf slides, Github Workflow: html, R, Rmd ChIPseq_stepBystep: html, R, Rmd |
2017‑07‑26 | 3.6/3.4 |
| Omics | Multi-omics data representation and analysis with MultiAssayExperiment, Marcel Ramos, Levi Waldron | BioC2017 | MAE lab: html, R, Rmd Github |
2017‑07‑26 | 3.6/3.4 |
| Advanced | Advanced R and Bioconductor, Martin Morgan, Hervé Pagès | U. Zurich | Inside the mind of R, R data and algorithms, S4 classes and methods, Doing R better | 2017‑06‑19 | 3.6/3.4 |
| Introduction | CSAMA: Statistical Analysis for Genome Scale Biology, Various authors | CSAMA2017 | Course material | 2017‑06‑11 | 3.5/3.4 |
| Introduction | Introduction to R and Bioconductor, Martin Morgan | OMRF | Install, Intro to R, Data input and manipulation, Statistics, Organization and Graphics, Intro to Bioconductor, Key classes and methods, An RNA-seq work flow, A ChIP-seq workflow | 2017‑05‑08 | 3.5/3.4 |
| Talk | Good software: simple, tidy, rich, Martin Morgan | Meetup | 2017‑04‑20 | 3.5/3.4 | |
| Introduction | Introduction to R and Bioconductor, Martin Morgan, Lori Shepherd | Moffitt | Install, Intro to R, Data input and manipulation, Statistics, Graphics, Intro to Bioconductor, Key classes and methods, An RNA-seq work flow, Next steps | 2017‑03‑02 | 3.4/3.3 |
| Packages | Software development in R and Bioconductor, Martin Morgan | UIdaho | Packages & version control | 2017‑01‑31 | 3.4/3.3 |
| Overview | R / Bioconductor for ‘Omics Analysis (U. Idaho), Martin Morgan | pdf (slides) | 2017‑01‑30 | 3.4/3.3 | |
| Introduction | Introduction to R, Martin Morgan | RPCI RIntro | Installation, Using R, Input and manipulation, Statistics, Workflows and visualization | 2017‑01‑09 | 3.4/3.3 |
| Overview | Bioconductor for ‘Omics Analysis (University of Rochester Medical Center), Martin Morgan | pdf (slides) | 2016‑12‑01 | 3.4/3.3 | |
| Annotation | Annotation, Communication, and Performance, Martin Morgan | Technion-BKU | html, R, Rmd | 2016‑11‑20 | 3.4/3.3 |
| RNAseq | An RNA-seq work flow, Martin Morgan | Technion-BKU | html, R, Rmd | 2016‑11‑20 | 3.4/3.3 |
| Introduction | Introduction to Bioconductor, Martin Morgan | Technion-BKU | html, R, Rmd | 2016‑11‑20 | 3.4/3.3 |
| Status | The Bioconductor Project: Current Status, Martin Morgan | BioC Asia | pdf (slides) | 2016‑11‑04 | 3.4/3.3 |
| Introduction | Bioconductor for Genomic Analysis, Martin Morgan | BioC Asia | html, R, Rmd, github | 2016‑11‑03 | 3.4/3.3 |
| Introduction | Reproducible Research in R / Bioconductor (CMRI, Sydney), Martin Morgan | html, R, Rmd, github | 2016‑10‑31 | 3.4/3.3 | |
| Overview | R / Bioconductor for ‘Omics Analysis (CMRI, Sydney), Martin Morgan | pdf (slides) | 2016‑10‑31 | 3.4/3.3 | |
| Introduction | Introduction to R and Bioconductor, Martin Morgan | CSAMA2016 | 2016‑07‑10 | 3.4/3.3 | |
| Statistics | Hypothesis testing, Wolfgang Huber | CSAMA2016 | 2016‑07‑10 | 3.4/3.3 | |
| Introduction | Learn to love the data frame, Jenny Bryan | CSAMA2016 | 2016‑07‑10 | 3.4/3.3 | |
| Statistics | Introduction to linear models, Levi Waldron | CSAMA2016 | 2016‑07‑10 | 3.4/3.3 | |
| Sequencing | High-throughput sequencing and using short-read aligners, Simon Anders | CSAMA2016 | 2016‑07‑10 | 3.4/3.3 | |
| RNAseq | RNA-seq data analysis and differential expression, Michael Love | CSAMA2016 | 2016‑07‑10 | 3.4/3.3 | |
| RNAseq | New RNA-seq workflows, Charlotte Soneson | CSAMA2016 | 2016‑07‑10 | 3.4/3.3 | |
| Genomic Ranges | Computing with sequences and ranges, Martin Morgan | CSAMA2016 | 2016‑07‑10 | 3.4/3.3 | |
| Experimental design | Experimental design, Charlotte Soneson | CSAMA2016 | 2016‑07‑10 | 3.4/3.3 | |
| Statistics | Clustering, classification, and regression with genomic examples, Vincent J. Carey | CSAMA2016 | 2016‑07‑10 | 3.4/3.3 | |
| Statistics | Robust statistics, Michael Love | CSAMA2016 | 2016‑07‑10 | 3.4/3.3 | |
| Statistics | Resampling methods, Levi Waldron | CSAMA2016 | 2016‑07‑10 | 3.4/3.3 | |
| Statistics | Multiple testing, Wolfgang Huber | CSAMA2016 | 2016‑07‑10 | 3.4/3.3 | |
| Annotation | Annotating genes, genomes, and variants, Martin Morgan | CSAMA2016 | 2016‑07‑10 | 3.4/3.3 | |
| Microbiome | Microbial genomics, Charlotte Soneson | CSAMA2016 | 2016‑07‑10 | 3.4/3.3 | |
| Graphics | Graphics, Wolfgang Huber | CSAMA2016 | 2016‑07‑10 | 3.4/3.3 | |
| Gene set enrichment | Gene set enrichment - Introduction, Martin Morgan | CSAMA2016 | 2016‑07‑10 | 3.4/3.3 | |
| Gene set enrichment | Gene-sets and correlation, Michael Love | CSAMA2016 | 2016‑07‑10 | 3.4/3.3 | |
| Statistics | Meta-analysis, Levi Waldron | CSAMA2016 | 2016‑07‑10 | 3.4/3.3 | |
| Performance | Performance and parallel evaluation, Martin Morgan | CSAMA2016 | 2016‑07‑10 | 3.4/3.3 | |
| Performance | Benchmarking out-of-memory strategies, Vincent J. Carey | CSAMA2016 | 2016‑07‑10 | 3.4/3.3 | |
| Intermediate | What should you do next?, Jenny Bryan | CSAMA2016 | 2016‑07‑10 | 3.4/3.3 | |
| Introduction | Introduction to R and Bioconductor, Martin Morgan | CSAMA2016 | html data Rmd | 2016‑07‑10 | 3.4/3.3 |
| Git | Use of Git and GitHub with R, RStudio, and R Markdown, Jenny Bryan | CSAMA2016 | 2016‑07‑10 | 3.4/3.3 | |
| RNAseq | End-to-end RNA-Seq workflow, Simon Anders; Michael Love; Charlotte Soneson | CSAMA2016 | Rmd html pdf | 2016‑07‑10 | 3.4/3.3 |
| Git | Reproducible research and R authoring with markdown and knitr, Jenny Bryan | CSAMA2016 | github | 2016‑07‑10 | 3.4/3.3 |
| ChIP-seq | ChIP-Seq analysis basics, Alejandro Reyes; Mike Smith | CSAMA2016 | Rmd html Rpackage | 2016‑07‑10 | 3.4/3.3 |
| Statistics | Independent Hypothesis Weighting, Wolfgang Huber | CSAMA2016 | Rmd html | 2016‑07‑10 | 3.4/3.3 |
| Performance | Machine Learning, Parallelization and performance, Martin Morgan; Vincent J. Carey | CSAMA2016 | Efficient and parallel code html Machine Learning html Rmd pdf Code |
2016‑07‑10 | 3.4/3.3 |
| Graphics | R Graphics, Wolfgang Huber | CSAMA2016 | Rmd pdf | 2016‑07‑10 | 3.4/3.3 |
| Introduction | Getting to know R and Bioconductor, Valerie Obenchain, Lori Shepherd | BioC2016 | Lecture Overview: html R Rmd github |
2016‑06‑25 | 3.4/3.3 |
| workflows | Building and running automated NGS analysis workflows, Thomas Girke | BioC2016 | SystemPipeR Intro: html R Rmd SystemPipeRdata: html R Rmd github |
2016‑06‑25 | 3.4/3.3 |
| Introduction | Introduction to ImmuneSpaceR, Renan Sauteraud, Lev Dashevskiy, Greg Finak, Raphael Gottardo | BioC2016 | Content: html R Rmd Example: html R Rmd github |
2016‑06‑25 | 3.4/3.3 |
| RNASeq | Analysis of single-cell RNA-seq data with R and Bioconductor, Davide Risso, Kelly Street, Michael Cole | BioC2016 | Cluster: html R Rmd Scone: html R Rmd Slingshot: html R Rmd github |
2016‑06‑25 | 3.4/3.3 |
| Intermediate | Writing efficient, scalable code, Martin Morgan | BioC2016 | HTML R Rmd github | 2016‑06‑25 | 3.4/3.3 |
| Annotation | Annotating high throughput data using Bioconductor resources, James MacDonald | BioC2016 | HTML R Rmd github | 2016‑06‑25 | 3.4/3.3 |
| Visualization | Interactive visualization with epiviz, Héctor Corrada Bravo, Jayaram kancherla, Justin Wagner | BioC2016 | Preprocessing: html R Rmd Minifi: html R Rmd github |
2016‑06‑25 | 3.4/3.3 |
| Gene set enrichment | Single Cell Differential Expression and Gene Set Enrichment with MAST, Andrew McDavid, Raphael Gottardo, Greg Finak | BioC2016 | Slides PDF R Rmd MAIT Analysis github |
2016‑06‑25 | 3.4/3.3 |
| Sequence Analysis | Managing big biological sequence data with Biostrings and DECIPHER, Erik Wright | BioC2016 | Slides html R Rmd github | 2016‑06‑25 | 3.4/3.3 |
| RNASeq | Low-level exploratory data analysis and methods development for RNA-seq, Michael Love | BioC2016 | HTML R Rmd github | 2016‑06‑25 | 3.4/3.3 |
| Genomic Ranges | Hello Ranges: An Introduction to Analyzing Genomic Ranges in R, Michael Lawrence | BioC2016 | PDF R Rmd github | 2016‑06‑25 | 3.4/3.3 |
| Omics | The MultiAssayExperiment class for analysis of multi-omics experiments, Levi Waldron, Marcel Ramos, Vince Carey, Kasper Hansen, Martin Morgan | BioC2016 | HTML R Rmd github | 2016‑06‑25 | 3.4/3.3 |
| RNASeq | Analyzing splice events from RNA-seq data with SGSeq, Leonard Goldstein | BioC2016 | HTML R Rmd github package |
2016‑06‑25 | 3.4/3.3 |
| Introductoin | Making your packages accessible to non-programmer collaborators using the VisRseq platform, Hamid Younesy, Torsten Möller, Mohammad M. Karimi | BioC2016 | Slides PDF R Rmd Software github |
2016‑06‑25 | 3.4/3.3 |
| Cloud | Wrapping Your R tools to Analyze National-Scale Cancer Genomics in the Cloud, Tengfei Yin, Nan Xiao | BioC2016 | api: html R Rmd apps: html R Rmd workflow: html R Rmd cgc-sparql: html R Rmd docker: html R Rmd rstudio: html R Rmd github |
2016‑06‑25 | 3.4/3.3 |
| Methylation | Analysing DNA methylation data with Bioconductor, Peter Hickey, Kasper Hansen | BioC2016 | HTML R Rmd github | 2016‑06‑25 | 3.4/3.3 |
| Statistics | Introduction to Bayesian Inference using Stan with Applications to Cancer Genomics, Jacqueline Buros | BioC2016 | Applied Survival Models: html R Rmd Survival Model Example: html R Rmd github |
2016‑06‑25 | 3.4/3.3 |
| Proteomics | R / Bioconductor tools for mass spectrometry-based proteomics, Laurent Gatto | BioC2016 | HTML R Rmd github | 2016‑06‑25 | 3.4/3.3 |
| Introduction | China R Conference: Bioconductor for high-throughput genetic data, Martin Morgan | China-R | 2016‑05‑29 | 3.3/3.3 | |
| Introduction | A1: R Intro, Martin Morgan, Lori Shepherd | BiocIntroRPCI | HTML R Rmd | 2016‑05‑16 | 3.3/3.3 |
| Introduction | A2: Input and Manipulation, Martin Morgan, Lori Shepherd | BiocIntroRPCI | HTML R Rmd | 2016‑05‑16 | 3.3/3.3 |
| Introduction | A3: Statistical Analysis, Martin Morgan, Lori Shepherd | BiocIntroRPCI | HTML R Rmd | 2016‑05‑16 | 3.3/3.3 |
| Introduction | A4: Visualization, Martin Morgan, Lori Shepherd | BiocIntroRPCI | HTML R Rmd | 2016‑05‑16 | 3.3/3.3 |
| Introduction | B1: Bioconductor Intro, Martin Morgan, Lori Shepherd | BiocIntroRPCI | HTML R Rmd | 2016‑05‑16 | 3.3/3.3 |
| Introduction | B2: Common Operations, Martin Morgan, Lori Shepherd | BiocIntroRPCI | HTML R Rmd | 2016‑05‑16 | 3.3/3.3 |
| Introduction | B3: RNASeq Workflow, Martin Morgan, Lori Shepherd | BiocIntroRPCI | HTML R Rmd | 2016‑05‑16 | 3.3/3.3 |
| Introduction | B4: Next Steps, Martin Morgan, Lori Shepherd | BiocIntroRPCI | HTML R Rmd | 2016‑05‑16 | 3.3/3.3 |
| Introduction | Introduction to High Throughput DNA Sequence Data Analysis Using R / Bioconductor, Martin Morgan | ENAR 2016 | Rmd R; github | 2016‑04‑08 | 3.2/3.2 |
| Introduction | Introduction to Sequence Analysis, R, and Bioconductor, Martin Morgan | EMBO 2015 | Content: html Rmd R; Exercises: html Rmd R; Notes: html Rmd R; github | 2015‑10‑19 | 3.2/3.2 |
| Microarrays | Gene Expression, Houtan Noushmehr | Uruguay2015 | HTML Rmd R | 2015‑10‑05 | 3.2/3.2 |
| Introduction | Data manipulation, Houtan Noushmehr | Uruguay2015 | HTML Rmd R | 2015‑10‑05 | 3.2/3.2 |
| Data Integration | The TCGAbiolinks package, Houtan Noushmehr | Uruguay2015 | 2015‑10‑05 | 3.2/3.2 | |
| Introduction | Introduction, Martin Morgan | Uruguay2015 | HTML Rmd R | 2015‑10‑05 | 3.2/3.2 |
| SummarizedExperiment | Working with Data: SummarizedExperiment, Martin Morgan | Uruguay2015 | HTML Rmd R | 2015‑10‑05 | 3.2/3.2 |
| Genomic Ranges | Genomic Ranges For Genome-Scale Data And Annotation, Martin Morgan | Uruguay2015 | HTML Rmd R | 2015‑10‑05 | 3.2/3.2 |
| Annotation | Adding Annotation To Your Analysis, Martin Morgan | Uruguay2015 | HTML Rmd R | 2015‑10‑05 | 3.2/3.2 |
| Large Data | Counting Reads And Working With Large Files, Martin Morgan | Uruguay2015 | HTML Rmd R | 2015‑10‑05 | 3.2/3.2 |
| RNASeq | RNA-Seq Differential Expression, Martin Morgan | Uruguay2015 | HTML Rmd R | 2015‑10‑05 | 3.2/3.2 |
| ChIPSeq | ChIP-Seq for Understanding Gene Regulation, Martin Morgan | Uruguay2015 | HTML Rmd R | 2015‑10‑05 | 3.2/3.2 |
| RNASeq | Supplement 1: RNA-Seq Workflow, Martin Morgan | Uruguay2015 | HTML Rmd R | 2015‑10‑05 | 3.2/3.2 |
| RNASeq | Supplement 2: RNA-Seq Statistical Issues, Martin Morgan | Uruguay2015 | HTML Rmd R | 2015‑10‑05 | 3.2/3.2 |
| Introduction | Introduction: Analysis and Comprehension, Martin Morgan | BiocAsia2015 | AMI, HTML, Rmd, R | 2015‑09‑07 | 3.2/3.2 |
| Data Representation | Workshop: Sequences, Alignments, and Large Data, Martin Morgan | BiocAsia2015 | AMI, HTML, Rmd, R | 2015‑09‑07 | 3.2/3.2 |
| RNASeq | Workshop: RNASeq, Martin Morgan | BiocAsia2015 | AMI, HTML, Rmd, R | 2015‑09‑07 | 3.2/3.2 |
| Annotation | Workshop: Gene, Genome, and Variant Annotation, Martin Morgan | BiocAsia2015 | AMI, HTML, Rmd, R | 2015‑09‑07 | 3.2/3.2 |
| ChIPSeq | Detecting differential binding in ChIP-seq data with csaw, Aaron Lun | BioC2015 | AMI, HTML, Rmd, R, GitHub | 2015‑07‑20 | 3.2/3.2 |
| Image Analysis | Basics of image data and spatial patterns analysis in R, Andrzej Oleś, Wolfgang Huber | BioC2015 | AMI, HTML, Rmd, R, GitHub | 2015‑07‑20 | 3.2/3.2 |
| Reproducibility | An introduction to Docker and the Bioconductor Docker containers, Dan Tenenbaum | BioC2015 | AMI, HTML, Rmd, R, GitHub | 2015‑07‑20 | 3.2/3.2 |
| Flow Cytometry | Visualize cytometry data with ggcyto, Greg Finak | BioC2015 | AMI, HTML, Rmd, R | 2015‑07‑20 | 3.2/3.2 |
| Flow Cytometry | Analysis of Designed Experiments Using OpenCyto, Greg Finak | BioC2015 | AMI, GitHub,HTML, Rmd, R | 2015‑07‑20 | 3.2/3.2 |
| Genomic Ranges | Practical introduction to Bioconductor foundational data structures for high throughput sequencing analysis, Hervé Pagès, Michael Lawrence | BioC2015 | AMI, PDF, R | 2015‑07‑20 | 3.2/3.2 |
| Best Practices | FAQ Live! Common questions and expert solutions, delivered in person, James MacDonald | BioC2015 | AMI, PDF, Rnw, R, GitHub | 2015‑07‑20 | 3.2/3.2 |
| Methylation | Methylation and the analysis of Illumina 450k microarrays, Kasper Hansen | BioC2015 | AMI, HTML, Rmd, R, GitHub | 2015‑07‑20 | 3.2/3.2 |
| RNASeq | SGSeq and alternative splicing, Leonard Goldstein | BioC2015 | AMI, HTML, Rmd, R, GitHub | 2015‑07‑20 | 3.2/3.2 |
| Omics | multiAssayQC, Levi Waldron, Tim Triche, Aedin Culhane | BioC2015 | AMI, GitHub, HTML, Rmd, R | 2015‑07‑20 | 3.2/3.2 |
| Omics | TCGAloading, Levi Waldron, Tim Triche, Aedin Culhane | BioC2015 | AMI, GitHub, HTML, Rmd, R | 2015‑07‑20 | 3.2/3.2 |
| Annotation | Annotation Resources for Bioconductor, Marc Carlson, Sonali Arora | BioC2015 | AMI, GitHub, HTML, Rmd, R | 2015‑07‑20 | 3.2/3.2 |
| Annotation | AnnotationHub Recipes, Marc Carlson, Sonali Arora | BioC2015 | AMI, GitHub, HTML, Rmd, R | 2015‑07‑20 | 3.2/3.2 |
| RNASeq | Differential expression, manipulation, and visualization of RNA-seq reads, Mike Love | BioC2015 | AMI, HTML, Rmd, R, GitHub | 2015‑07‑20 | 3.2/3.2 |
| Scalable Computing | GoogleGenomics, Nicole Deflaux, Siddhartha Bagaria and Craig Citro | BioC2015 | AMI, GitHub, readthedocs | 2015‑07‑20 | 3.2/3.2 |
| Workflows | Automated NGS workflows with systemPipeR running on clusters or single machines, with a focus on VAR-seq: systemPipeR, Thomas Girke | BioC2015 | AMI, GitHub, HTML, Rmd, R | 2015‑07‑20 | 3.2/3.2 |
| Large Data | Management and analysis of large genomic data., Valerie Obenchain, Martin Morgan | BioC2015 | AMI, HTML, Rmd, R, GitHub | 2015‑07‑20 | 3.2/3.2 |
| Introduction | Introduction to R, Sonali Arora | BioC2015 | AMI, GitHub, HTML, Rmd, R | 2015‑07‑20 | 3.2/3.2 |
| Introduction | Introduction to Bioconductor, Sonali Arora | BioC2015 | AMI, GitHub, HTML, Rmd, R | 2015‑07‑20 | 3.2/3.2 |
| Introduction | Lab: Basic Bioconductor, Sonali Arora | BioC2015 | AMI, GitHub, HTML, Rmd, R | 2015‑07‑20 | 3.2/3.2 |
| Intermediate | Lab: Intermediate Bioconductor, Sonali Arora | BioC2015 | AMI, GitHub, HTML, Rmd, R | 2015‑07‑20 | 3.2/3.2 |
| RNASeq | Advanced Lab: Explore the Data, Sonali Arora | BioC2015 | AMI, GitHub, HTML, Rmd, R | 2015‑07‑20 | 3.2/3.2 |
| RNASeq | Advanced RnaSeq, Sonali Arora | BioC2015 | AMI, GitHub, HTML, Rmd, R | 2015‑07‑20 | 3.2/3.2 |
| Workflows | Liftr & sbgr, Nan Xiao | BioC2015 | AMI, PDF, Video | 2015‑07‑20 | 3.2/3.2 |
| Introduction | Bioconductor for high-throughput sequence analysis, Martin Morgan, Sonali Arora | useR! 2015 | talk, lab; github | 2015‑06‑30 | 3.1/3.2 |
| Introduction | Lab: Introduction to R and Bioconductor, Martin Morgan | CSAMA 2015 | html; github | 2015‑06‑15 | 3.1/3.2 |
| ReproducibleResearch | Lab: Reproducible Research and R Authoring with markdown and knitr, Laurent Gatto | CSAMA 2015 | html; github | 2015‑06‑15 | 3.1/3.2 |
| RNASeq | Lab: End-to-end RNA-Seq workflow, Mike Love, Simon Anders, Wolfgang Huber | CSAMA 2015 | html; github | 2015‑06‑15 | 3.1/3.2 |
| ChIPSeq | Lab: ChIP-seq analysis basics, Aleksandra Pȩkowska, Simon Anders | CSAMA 2015 | pdf; github | 2015‑06‑15 | 3.1/3.2 |
| Visualization | Lab: Interactive data visualization with Shiny, Andrzej Oleś | CSAMA 2015 | html; github | 2015‑06‑15 | 3.1/3.2 |
| LargeData | Lab: Performance and Parallel Evaluation, Martin Morgan | CSAMA 2015 | html; github | 2015‑06‑15 | 3.1/3.2 |
| MachineLearning | Lab: Machine Learning and Parallel Computing, Wolfgang Huber, Martin Morgan | CSAMA 2015 | html; github | 2015‑06‑15 | 3.1/3.2 |
| Variants | Lab: Plotting Regions from BAM files directly, Paul Pyl | CSAMA 2015 | html; github | 2015‑06‑15 | 3.1/3.2 |
| Metagenomics | Lab: Phyloseq Basic Usage for Metagenomics, Paul Pyl | CSAMA 2015 | html; github | 2015‑06‑15 | 3.1/3.2 |
| Introduction | Lecture: Introduction to R and Bioconductor, Martin Morgan | CSAMA 2015 | 2015‑06‑15 | 3.1/3.2 | |
| Technology | Lecture: Basics of sequence alignment and aligners, Simon Anders | CSAMA 2015 | 2015‑06‑15 | 3.1/3.2 | |
| Statistics | Lecture: Hypothesis testing and multiple testing, Wolfgang Huber | CSAMA 2015 | 2015‑06‑15 | 3.1/3.2 | |
| Statistics | Lecture: Clustering and classification, Vincent Carey | CSAMA 2015 | html | 2015‑06‑15 | 3.1/3.2 |
| RNASeq | Lecture: RNA-Seq data analysis and differential expression part I, Simon Anders | CSAMA 2015 | 2015‑06‑15 | 3.1/3.2 | |
| RNASeq | Lecture: RNA-Seq data analysis and differential expression part II, Michael Love | CSAMA 2015 | 2015‑06‑15 | 3.1/3.2 | |
| GenomicRanges | Lecture: Computing with sequences and genomic intervals, Martin Morgan | CSAMA 2015 | pdf, html | 2015‑06‑15 | 3.1/3.2 |
| ChIPSeq | Lecture: Epigenetics and ChIP-Seq, Aleksandra Pȩkowska | CSAMA 2015 | 2015‑06‑15 | 3.1/3.2 | |
| Proteomics | Lecture: Introduction to MS based proteomics and Bioconductor infrastructure, Laurent Gatto | CSAMA 2015 | 2015‑06‑15 | 3.1/3.2 | |
| RNASeq | Lecture: Single-cell RNA-Seq, Alejandro Reyes, Simon Anders | CSAMA 2015 | 2015‑06‑15 | 3.1/3.2 | |
| HiC | Lecture: HiC data analysis, Aleksandra Pȩkowska | CSAMA 2015 | 2015‑06‑15 | 3.1/3.2 | |
| Visualization | Lecture: Visualization, the grammar of graphics and ggplot2, Wolfgang Huber | CSAMA 2015 | 2015‑06‑15 | 3.1/3.2 | |
| Annotation | Lecture: Working with annotation - genes, genomic features and variants, Martin Morgan | CSAMA 2015 | pdf, html | 2015‑06‑15 | 3.1/3.2 |
| GeneSetEnrichment | Lecture: Gene set enrichment analysis, part I, Martin Morgan | CSAMA 2015 | 2015‑06‑15 | 3.1/3.2 | |
| GeneSetEnrichment | Lecture: Gene set enrichment analysis, part II, Michael Love | CSAMA 2015 | html | 2015‑06‑15 | 3.1/3.2 |
| LargeData | Lecture: Large data, performance, and parallelization; large-scale efficient computation with genomic intervals, Martin Morgan | CSAMA 2015 | 2015‑06‑15 | 3.1/3.2 | |
| MOOC | Introduction to Bioconductor, Rafael Irizarry, Michael Love, Vincent Carey | EdX-PH525.4x | html | 2015‑03‑30 | 3.1/3.2 |
| MOOC | Statistics and R for the Life Sciences, Rafael Irizarry, Michael Love | EdX-PH525.1x | html | 2015‑01‑19 | 3.1/3.2 |
| Intermediate | Use R / Bioconductor for Sequence Analysis, Martin Morgan, Sonali Arora | SeattleApr2015 | package, AMI | 2015‑04‑06 | 3.1/3.2 |
| Genomic Ranges | Genomic Ranges, Martin Morgan | SeattleApr2015 | html, R, Rmd | 2015‑04‑06 | 3.1/3.2 |
| RNASeq | Differential Gene Expression, Martin Morgan | SeattleApr2015 | html, R, Rmd | 2015‑04‑06 | 3.1/3.2 |
| Machine Learning | Machine Learning, Sonali Arora | SeattleApr2015 | html, R, Rmd | 2015‑04‑06 | 3.1/3.2 |
| Gene set enrichment | Gene set enrichment, Martin Morgan | SeattleApr2015 | html, R, Rmd | 2015‑04‑06 | 3.1/3.2 |
| ChIPSeq | ChIP-seq with csaw, Martin Morgan | SeattleApr2015 | html, R, Rmd | 2015‑04‑06 | 3.1/3.2 |
| Methylation | Methylation and regulatory work flows with minfi, Martin Morgan | SeattleApr2015 | html, R, Rmd | 2015‑04‑06 | 3.1/3.2 |
| Large Data | Integrative Data Analysis, Martin Morgan | SeattleApr2015 | html, R, Rmd | 2015‑04‑06 | 3.1/3.2 |
| Large Data | Large Data, Martin Morgan | SeattleApr2015 | htm, R, Rmd | 2015‑04‑06 | 3.1/3.2 |
| Intermediate | Use R / Bioconductor for Sequence Analysis, Martin Morgan, Hervé Pagès | Use Bioc | package, AMI | 2015‑02‑04 | 3.1/3.2 |
| Introduction | Introduction to R / Bioconductor, Martin Morgan, Hervé Pagès | Use Bioc | html, R, Rmd | 2015‑02‑04 | 3.1/3.2 |
| Genomic Ranges | Genomic Ranges, Martin Morgan, Hervé Pagès | Use Bioc | html, R, Rmd, slides | 2015‑02‑04 | 3.1/3.2 |
| Status Update | New packages and functionality, Martin Morgan, Hervé Pagès | Use Bioc | html, R, Rmd | 2015‑02‑04 | 3.1/3.2 |
| Large Data | Working with large data, Martin Morgan, Hervé Pagès | Use Bioc | html, R, Rmd | 2015‑02‑04 | 3.1/3.2 |
| Annotation | Package, web, and hub annotation resources, Martin Morgan, Hervé Pagès | Use Bioc | html, R, Rmd | 2015‑02‑04 | 3.1/3.2 |
| Visualization | Interactive visualization, Martin Morgan, Hervé Pagès | Use Bioc | html, R, Rmd | 2015‑02‑04 | 3.1/3.2 |
| Introduction | Learning R / Bioconductor for Sequence Analysis, Martin Morgan, Hervé Pagès | Learn Bioc | package, AMI | 2015‑02‑02 | 3.1/3.2 |
| R | Introduction to R, Martin Morgan, Hervé Pagès | Learn Bioc | html, R, Rmd | 2015‑02‑02 | 3.1/3.2 |
| Bioconductor | Introduction to Bioconductor, Martin Morgan, Hervé Pagès | Learn Bioc | html, R, Rmd | 2015‑02‑02 | 3.1/3.2 |
| Sequence Analysis | Introduction to Bioconductor for Sequence Analysis, Martin Morgan, Hervé Pagès | Learn Bioc | html, R, Rmd | 2015‑02‑02 | 3.1/3.2 |
| RNASeq | RNA-seq overview and work flow, Martin Morgan, Hervé Pagès | Learn Bioc | slides, lab, R, Rmd | 2015‑02‑02 | 3.1/3.2 |
| Sequence Analysis | Overview of common sequencing work flows, Martin Morgan, Hervé Pagès | Learn Bioc | html, R, Rmd | 2015‑02‑02 | 3.1/3.2 |
| Large Data | Working with large data, Martin Morgan, Hervé Pagès | Learn Bioc | html, R, Rmd | 2015‑02‑02 | 3.1/3.2 |
| Packages | From code to packages, Martin Morgan, Hervé Pagès | Learn Bioc | html, R, Rmd | 2015‑02‑02 | 3.1/3.2 |
| Reproducibility | Introduction to reproducible analysis, Martin Morgan, Hervé Pagès | Learn Bioc | html, R, Rmd | 2015‑02‑02 | 3.1/3.2 |
| Visualization | Visualizing genomic data, Martin Morgan, Hervé Pagès | Learn Bioc | html, R, Rmd | 2015‑02‑02 | 3.1/3.2 |
| Introduction | R/Bioconductor for Integrative Genomic Analysis, Martin Morgan | useR! Lyon | slides | 2015‑01‑15 | 3.0/3.1.2 |
| Status Update | Bioconductor Project Update, January 2015, Martin Morgan | BiocEurope2015 | slides | 2015‑01‑12 | 3.1/3.2 |
| Best Practices | Google Hangout for New Package Submitters, Marc Carlson | NewPackages | slides, Video | 2014‑12‑10 | 3.1/3.2 |
| Appendix | Appendix: Install IGV, Martin Morgan | SeattleOct2014 | html, R, Rmd hg19_alias.tab | 2014‑10‑27 | 3.0/3.1.1 |
| Visualization | Visualization, Martin Morgan | SeattleOct2014 | html, R, Rmd | 2014‑10‑27 | 3.0/3.1.1 |
| Reproducibility | Reproducible Research, Martin Morgan | SeattleOct2014 | html, R, Rmd | 2014‑10‑27 | 3.0/3.1.1 |
| Packages | Organizing Code in Functions, Files, and Packages, Martin Morgan | SeattleOct2014 | html, R, Rmd | 2014‑10‑27 | 3.0/3.1.1 |
| Large Data | Working with Large Data, Martin Morgan | SeattleOct2014 | html, R, Rmd | 2014‑10‑27 | 3.0/3.1.1 |
| Gene set enrichment | Gene set enrichment, Martin Morgan | SeattleOct2014 | html, R, Rmd | 2014‑10‑27 | 3.0/3.1.1 |
| Annotation | Annotating Genes, Genomes, and Variants, Martin Morgan | SeattleOct2014 | html, R, Rmd | 2014‑10‑27 | 3.0/3.1.1 |
| Machine Learning | Machine Learning, Sonali Arora | SeattleOct2014 | html, R, Rmd | 2014‑10‑27 | 3.0/3.1.1 |
| Workflows | Common Sequence Analysis Work Flows, Martin Morgan | SeattleOct2014 | html, R, Rmd | 2014‑10‑27 | 3.0/3.1.1 |
| Copy Number | Copy Number, Sonali Arora | SeattleOct2014 | html, R, Rmd | 2014‑10‑27 | 3.0/3.1.1 |
| RNASeq | RNA-Seq, Martin Morgan | SeattleOct2014 | html, R, Rmd | 2014‑10‑27 | 3.0/3.1.1 |
| RNASeq | RNA-Seq Lab: Workflow – gene-level exploratory analysis and differential expression, Michael Love et al. | SeattleOct2014 | html | 2014‑10‑27 | 3.0/3.1.1 |
| Bioconductor | Introduction to Bioconductor, Martin Morgan | SeattleOct2014 | html, R, Rmd | 2014‑10‑27 | 3.0/3.1.1 |
| Introduction | Introduction, Martin Morgan | SeattleOct2014 | html, R, Rmd | 2014‑10‑27 | 3.0/3.1.1 |
| R | Introduction to R, Martin Morgan | SeattleOct2014 | html, R, Rmd | 2014‑10‑27 | 3.0/3.1.1 |
| R | Introduction to R (slides), Martin Morgan | Epigenomics | html | 2014‑08‑24 | 2.14/3.1.1 |
| Epigenomics | Introduction to Bioconductor for Epigneomics, Martin Morgan | Epigenomics | pdf R Rnw | 2014‑08‑24 | 2.14/3.1.1 |
| Sequence Analysis | Introduction to Bioconductor for Sequence Analysis, Martin Morgan | Epigenomics | html R Rmd | 2014‑08‑24 | 2.14/3.1.1 |
| Data Representation | Sequence data represenations in Bioconductor, Martin Morgan | Epigenomics | html R Rmd | 2014‑08‑24 | 2.14/3.1.1 |
| RNASeq | Introduction to RNA-Seq data analysis, Benilton Carvalho | Epigenomics | 2014‑08‑24 | 2.14/3.1.1 | |
| RNASeq | Counting reads for RNA-seq in Bioconductor, Martin Morgan | Epigenomics | pdf R Rnw | 2014‑08‑24 | 2.14/3.1.1 |
| Methylation | Introduction to working with methylation arrays (slides), Martin Morgan | Epigenomics | html | 2014‑08‑24 | 2.14/3.1.1 |
| Methylation | A short methylation analysis using minfi, Martin Morgan | Epigenomics | html R Rmd | 2014‑08‑24 | 2.14/3.1.1 |
| eQTL | eQTL analysis – an approach with Bioconductor, Vincent Carey | Epigenomics | 2014‑08‑24 | 2.14/3.1.1 | |
| R/Bioconductor | R / Bioconductor for everyone, Martin Morgan | BioC2014 | slides, pdf, R | 2014‑07‑30 | 2.14/3.1.1 |
| Genomic Ranges | Learn how to use Bioconductor to perform common tasks on your high-throughput sequencing data, Hervé Pagès | BioC2014 | 2014‑07‑30 | 2.14/3.1.1 | |
| Annotation | Bioconductor annotations: using and sharing resources, Marc Carlson | BioC2014 | workflow, vignette | 2014‑07‑30 | 2.14/3.1.1 |
| Scalable Computing | Parallel Computing with Bioconductor in the Amazon Cloud, Valerie Obenchain | BioC2014 | pdf, R | 2014‑07‑30 | 2.14/3.1.1 |
| Variants | Variant calling with Bioconductor, Michael Lawrence | BioC2014 | pdf, R, pkg | 2014‑07‑30 | 2.14/3.1.1 |
| RNASeq | Differential gene- and exon-level expression analyses for RNA-seq data using edgeR, voom and featureCounts, Mark Robinson | BioC2014 | pdf, html, md | 2014‑07‑30 | 2.14/3.1.1 |
| RNASeq | Analysis of RNA-Seq using the DESeq2 package, Michael Love | BioC2014 | pdf, Rnw, R | 2014‑07‑30 | 2.14/3.1.1 |
| RNASeq | CRISPRseek: Design of target-specific guide RNAs in CRISPR-Cas9 genome-editing systems, Julie Zhu | BioC2014 | pdf, html, Rmd, R | 2014‑07‑30 | 2.14/3.1.1 |
| Flow Cytometry | Tutorial, Introduction to Flow Cytometry Data Analysis using OpenCyto and Bioconductor, Greg Finak | BioC2014 | html, Rmd, R | 2014‑07‑30 | 2.14/3.1.1 |
| Methylation | Analysis of 450k methylation data with the minfi package, Kasper Hansen | BioC2014 | pdf, Rnw, R | 2014‑07‑30 | 2.14/3.1.1 |
| ChIPSeq | Visualisation and assessment of ChIP-seq quality using ChIPQC and Diffbind packages, Tom Carroll | BioC2014 | pdf, R | 2014‑07‑30 | 2.14/3.1.1 |
| eQTL | Genetics of gene expression: computation and integrative prediction, Vincent Carey | BioC2014 | html, Rmd, R | 2014‑07‑30 | 2.14/3.1.1 |
| Proteomics | R / Bioconductor packages for Proteomics, Laurent Gatto | BioC2014 | html, Rmd, R | 2014‑07‑30 | 2.14/3.1.1 |
| Meta-analysis | Meta-analysis of genomics experiments using Bioconductor, Levi Waldron | BioC2014 | Rpres, R | 2014‑07‑30 | 2.14/3.1.1 |
| Pathway | Integrated pathway analysis of multiple omics datasets, Aedin Culhane | BioC2014 | html, Rmd, R | 2014‑07‑30 | 2.14/3.1.1 |
| R/Bioconductor | Trends in Genomic Data Analysis in R, Levi Waldron | ISMB2014 | 2014‑07‑15 | 2.14/3.1.1 | |
| Annotation | Accessing Annotation Resources, Martin Morgan | ISMB2014 | pdf, R, R | 2014‑07‑15 | 2.14/3.1.1 |
| Scalable Computing | Scalable Integrative Bioinformatics with Bioconductor, Vincent Carey | ISMB2014 | pptx | 2014‑07‑15 | 2.14/3.1.1 |
| RNASeq | Analysis of RNA-Seq Data, Mike Love | ISMB2014 | html | 2014‑07‑15 | 2.14/3.1.1 |
| R/Bioconductor | Introduction to R / Bioconductor, Martin Morgan | useR2014 | html, R | 2014‑06‑30 | 2.14/3.1.0 |
| Data Representation | Sequence Data Representation, Martin Morgan | useR2014 | html, R | 2014‑06‑30 | 2.14/3.1.0 |
| Annotation | Annotations, Martin Morgan | useR2014 | html, R | 2014‑06‑30 | 2.14/3.1.0 |
| RNASeq | Work flows : RNA-Seq, Martin Morgan | useR2014 | html, R | 2014‑06‑30 | 2.14/3.1.0 |
| R/Bioconductor | Working with R, Martin Morgan | SeattleFeb2014 | pdf, R, Rnw | 2014‑02‑27 | 2.14/3.1.0 |
| R/Bioconductor | Bioconductor - Slides, Martin Morgan | SeattleFeb2014 | pdf, Rnw, R | 2014‑02‑27 | 2.14/3.1.0 |
| Data Representation | Genomic Ranges - Slides, Martin Morgan | SeattleFeb2014 | pdf, Rnw, R | 2014‑02‑27 | 2.14/3.1.0 |
| Data Representation | Working with DNA Sequences, Sonali Arora | SeattleFeb2014 | pdf, Rnw, R | 2014‑02‑27 | 2.14/3.1.0 |
| Genomic Ranges | Working with FASTQ, BAM, and VCF files, Martin Morgan | SeattleFeb2014 | pdf, Rnw, R | 2014‑02‑27 | 2.14/3.1.0 |
| Genomic Ranges | Working with Genomic Ranges, Martin Morgan | SeattleFeb2014 | pdf, Rnw, R | 2014‑02‑27 | 2.14/3.1.0 |
| Annotation | RNASeq Analysis, Martin Morgan | SeattleFeb2014 | pdf, Rnw, R | 2014‑02‑27 | 2.14/3.1.0 |
| Visualization | Working with Annotations, Martin Morgan | SeattleFeb2014 | pdf, Rnw, R | 2014‑02‑27 | 2.14/3.1.0 |
| RNASeq | Visualization of Genomic Data, Sonali Arora | SeattleFeb2014 | pdf, Rnw, R | 2014‑02‑27 | 2.14/3.1.0 |
| Annotation | Annotations, Martin Morgan | SeattleFeb2014 | pdf,R, Rnw | 2014‑02‑27 | 2.14/3.1.0 |
| R/Bioconductor | Bioconductor, Martin Morgan | summerx | pdf, R, Rnw | 2014‑01‑27 | 2.14/3.1.0 |
| Genomic Ranges | Ranges, Hervé Pagès | summerx | pdf, R, Rnw | 2014‑01‑27 | 2.14/3.1.0 |
| Annotation | Annotations, Martin Morgan | summerx | pdf, R, Rnw | 2014‑01‑27 | 2.14/3.1.0 |
| Variants | Variants, Martin Morgan | summerx | pdf, Rnw | 2014‑01‑27 | 2.14/3.1.0 |
| Visualization | Visualization., Martin Morgan | summerx | pdf, R, Rnw | 2014‑01‑27 | 2.14/3.1.0 |
| Best Practices | Best Practices for Managing R / Bioconductor Scripts, Martin Morgan | summerx | pdf, Rnw | 2014‑01‑27 | 2.14/3.1.0 |
| R/Bioconductor | Accessing resources - packages, classes, methods, and efficient code, Martin Morgan | CSAMA2014 | html, R | 2014‑06‑22 | 2.14/3.1.1 |
| Genomic Ranges | Computing with genomic ranges, sequences and alignments, Michael Lawrence | CSAMA2014 | 2014‑06‑22 | 2.14/3.1.1 | |
| Annotation | Working with gene and genome annotations, Martin Morgan | CSAMA2014 | pdf, R | 2014‑06‑22 | 2.14/3.1.1 |
| Visualization | Visualisation in Statistical Genomics, Vincent Carey | CSAMA2014 | 2014‑06‑22 | 2.14/3.1.1 | |
| Statistics | Elements of statistics 1: t-test and linear model, Robert Gentleman | CSAMA2014 | 2014‑06‑22 | 2.14/3.1.1 | |
| Statistics | Elements of statistics 2: multiple testing, false discovery rates, independent filtering, Wolfgang Huber | CSAMA2014 | 2014‑06‑22 | 2.14/3.1.1 | |
| Statistics | Elements of statistics 3: Classification and clustering - basic concepts, Unknown | CSAMA2014 | html | 2014‑06‑22 | 2.14/3.1.1 |
| Statistics | Elements of statistics 4: regularisation & kernels, Wolfgang Huber | CSAMA2014 | 2014‑06‑22 | 2.14/3.1.1 | |
| Statistics | Elements of statistics 5: experimental design, Simon Anders | CSAMA2014 | 2014‑06‑22 | 2.14/3.1.1 | |
| RNASeq | A complete RNA-Seq differential expression workflow, Michael Love, Simon Anders, Wolfgang Huber | CSAMA2014 | pdf, R | 2014‑06‑22 | 2.14/3.1.1 |
| RNASeq | RNA-Seq 1: differential expression analysis - GLMs and testing, Simon Anders | CSAMA2014 | 2014‑06‑22 | 2.14/3.1.1 | |
| RNASeq | RNA-Seq 3: alternative exon usage, Alejandro Reyes | CSAMA2014 | 2014‑06‑22 | 2.14/3.1.1 | |
| DNASeq | DNA-Seq 1: Variant calling, Michael Lawrence | CSAMA2014 | 2014‑06‑22 | 2.14/3.1.1 | |
| DNASeq | DNA-Seq 2: visualisation and quality assessment of variant calls, Paul Theodor Pyl | CSAMA2014 | 2014‑06‑22 | 2.14/3.1.1 | |
| ChIPSeq | ChIP-seq Analysis, Martin Morgan | CSAMA2014 | pdf, R | 2014‑06‑22 | 2.14/3.1.1 |
| Proteomics | Proteomics, Laurent Gatto | CSAMA2014 | 2014‑06‑22 | 2.14/3.1.1 | |
| Visualization | Image Analysis, Susan Holmes, Wolfgang Huber, Trevor Martin | CSAMA2014 | 2014‑06‑22 | 2.14/3.1.1 | |
| eQTL / molecular-QTL | eQTL / molecular-QTL analyses, Vincent Carey | CSAMA2014 | 2014‑06‑22 | 2.14/3.1.1 | |
| Gene set enrichment | Gene set enrichment analysis, Robert Gentleman | CSAMA2014 | 2014‑06‑22 | 2.14/3.1.1 | |
| Introduction | Introduction to R and Bioconductor, Martin Morgan | CSAMA2014 | 2014‑06‑22 | 2.14/3.1.1 | |
| RNASeq | High-throughput sequencing: Alignment and related topic, Simon Anders | CSAMA2014 | 2014‑06‑22 | 2.14/3.1.1 | |
| Variants | Variant tallies, visualisation, HDF5, Paul Theodor Pyl | CSAMA2014 | pdf, R | 2014‑06‑22 | 2.14/3.1.1 |
| Annotation | Working with Ranges infrastructure: annotating and understanding regions, Martin Morgan | CSAMA2014 | pdf, R | 2014‑06‑22 | 2.14/3.1.1 |
| Reporting | Reporting your analysis - authoring knitr/Rmarkdown, ReportingTools, shiny, Laurent Gatto | CSAMA2014 | pkg | 2014‑06‑22 | 2.14/3.1.1 |
Courses by year
Custom workshops
The Bioconductor project can provide customized workshops on statistical methods and software for the analysis of genomic data for different educational and industrial clients. Interested parties should contact Vincent Carey.
