R / Bioconductor for High-Throughput Sequence Analysis

I would like to recommend a recent workshop material on R/Bioconductor from Marc Carlson et al.

http://www.bioconductor.org/help/course-materials/2013/SeattleMay2013/

PDF: IntermediateSequenceAnalysis2013.pdf
R script: IntermediateSequenceAnalysis2013.R

Here is the TOC list if you want to read more (highlight for suggested reading list):

Interesting packages of new BioC2.7

NuPoP

Nucleosome positioning prediction

Mulcom

Differential expression and false discovery rate calculation through multiple comparison

ontoCAT

Ontology parsing

BHC

Bayesian Hierarchical Clustering

iSeq

Bayesian Hierarchical Modeling of ChIP-seq Data Through Hidden Ising Models

URL: http://bioconductor.org/news/bioc_2_7_release/

btw, other interesting ones in BioC 2.6:

New sequence analysis tools address infrastructure (GenomicRanges, Rsamtools, girafe); ChIP-seq (BayesPeak, CSAR, PICS); digital gene expression and RNA-seq (DESeq, goseq, segmentSeq); and motif discovery (MotIV, rGADEM).