Boston Bioconductor Basics April 4-5 2013

A two-day course will be offered at the Inn at Longwood, 342 Longwood Ave, Boston, 4-5 April 2013. Tuition $450 academic, $750 commercial.

Instructor: Vince J Carey, Channing Division of Network Medicine, Harvard Medical School

Registration form. To register, print out the form linked at the beginning of this paragraph, fill in completely, and send form with remittance or documentation of payment to the address noted on the form. Space is limited. Individuals attempting on-site registration may be asked to leave owing to occupancy limitations that are strictly enforced.

Course format: Modules as defined in the syllabus below are treated with brief slide-based lectures followed by self- or team-worked problems with review at end of module period. Preparatory notes will be supplied to all students prior to the course. Some tutorial background on statistics and R will be provided, and relevant papers in modern genomics will be identified to help students grasp the scope of the course before applying/attending. Relevant links will be provided here soon.

Computing support: The hotel provides wifi connections, but there is no guarantee of sufficient bandwidth to support nontrivial web usage. Students must bring a working laptop with R 2.15.2 along with a set of Bioconductor/CRAN packages installed and tested. Code to install and test will be posted here prior to the course. There will be minimal if any support for out-of-date or improperly configured, untested environments on laptops. Power strips will be supplied.

Tentative syllabus:

April 4 2013

0900-1030 R review: data input, statistical modeling, scripts and functions
1045-1200 Annotation: genes, gene sets, SNPs, tracks, GRanges
1200-1300 Lunch on your own
1300-1400 Representing genome-scale data with R: ExpressionSet, SummarizedExperiment, VCF, BamViews
1400-1500 Visualization for genome-scale data: ggplot2, Gviz, rtracklayer
1530-1700 Capture, preprocessing, and differential expression with DNA microarrays: GEOquery, affy, lumi, sva, limma; Special topic: eQTL

April 5 2013

0900-1000 Advanced considerations for computing with R: Amazon EC2, cluster and multicore computing: foreach, DoParallel, BiocParallel
1000-1200 Capture and QA of high-throughput sequencing experiments: ShortRead, Rsamtools
1200-1300 Lunch on your own
1300-1400 DNA variants: VariantTools, VariantAnnotation, GWAStools
1400-1500 Protein-DNA binding data: chipseq, ChIPpeakAnno
1530-1700 RNA-seq: DESeq, DEXSeq, edgeR, cummeRbund

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