[BioC] Course: Learning R / Bioconductor for Sequence Analysis, Seattle, WA Oct 27-29

[Dale N. Richardson]

Seconded! An online version of the course would be indispensable. 

......................................................................................................
Dale Richardson, Ph.D.

Laboratory of Plant Molecular Biology
Instituto Gulbenkian de Ciência
Rua da Quinta Grande, 6
2780-156 Oeiras
Portugal
http://www.igc.gulbenkian.pt

Tel: +351 967 992 816
Email: drichardson at igc.gulbenkian.pt




On 15/09/2014, at 17:27, Son Pham <spham at salk.edu> wrote:

> Thanks Martin for offering the course. It's fantastics -- and if it would
> be an online course, like coursera, it will also be great for a lot of
> distant people.
> 
> -Son.
> 
> 
> 
> 
> 
> Son Pham, Ph.D
> cseweb.ucsd.edu/~kspham/
> 
> On Mon, Sep 15, 2014 at 7:13 AM, Martin Morgan <mtmorgan at fhcrc.org> wrote:
> 
>> Course: Learning R / Bioconductor for Sequence Analysis
>> 
>> Dates: October 27-29, Seattle, WA.
>> 
>> Registration: https://register.bioconductor.org/Seattle-Oct-2014/
>> 
>> This course is directed at beginning and intermediate users who would like
>> an introduction to the analysis and comprehension of high-throughput
>> sequence data using R and Bioconductor. Day 1 focuses on learning essential
>> background: an introduction to the R programming language; central concepts
>> for effective use of Bioconductor software; and an overview of
>> high-throughput sequence analysis work flows. Day 2 emphasizes use of
>> Bioconductor for specific tasks: an RNA-seq differential expression work
>> flow; exploratory, machine learning, and other statistical tasks; gene set
>> enrichment; and annotation. Day 3 transitions to understanding effective
>> approaches for managing larger challenges: strategies for working with
>> large data, writing re-usable functions, developing reproducible reports
>> and work flows, and visualizing results. The course combines lectures with
>> extensive hands-on practicals; students are required to bring a laptop with
>> wireless internet access and a modern version of the Chrome or Safari web
>> browser.
>> --
>> Computational Biology / Fred Hutchinson Cancer Research Center
>> 1100 Fairview Ave. N.
>> PO Box 19024 Seattle, WA 98109
>> 
>> Location: Arnold Building M1 B861
>> Phone: (206) 667-2793
>> 
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>> 
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