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

"Dale N. Richardson" <drichardson-Fe/[email protected]> Mon, 15 Sep 2014 17:34:56 +0100
Newsgroups gmane.science.biology.informatics.conductor,gmane.science.biology.informatics.conductor.devel
Message-ID <[email protected]>
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Seconded! An online version of the course would be indispensable.=20

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

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

Tel: +351 967 992 816
Email: drichardson-Fe/[email protected]




On 15/09/2014, at 17:27, Son Pham <spham-xrR1t/[email protected]> 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.
>=20
> -Son.
>=20
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> Son Pham, Ph.D
> cseweb.ucsd.edu/~kspham/
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> On Mon, Sep 15, 2014 at 7:13 AM, Martin Morgan <[email protected]> wrote:
>=20
>> Course: Learning R / Bioconductor for Sequence Analysis
>>=20
>> Dates: October 27-29, Seattle, WA.
>>=20
>> Registration: https://register.bioconductor.org/Seattle-Oct-2014/
>>=20
>> This course is directed at beginning and intermediate users who would li=
ke
>> an introduction to the analysis and comprehension of high-throughput
>> sequence data using R and Bioconductor. Day 1 focuses on learning essent=
ial
>> background: an introduction to the R programming language; central conce=
pts
>> 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 s=
et
>> 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 wi=
th
>> extensive hands-on practicals; students are required to bring a laptop w=
ith
>> 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
>>=20
>> Location: Arnold Building M1 B861
>> Phone: (206) 667-2793
>>=20
>> _______________________________________________
>> Bioconductor mailing list
>> [email protected]
>> https://stat.ethz.ch/mailman/listinfo/bioconductor
>> Search the archives: http://news.gmane.org/gmane.
>> science.biology.informatics.conductor
>>=20
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