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Introduction to R/Bioconductor

Introduction to R/Bioconductor. Pieta Schofield. Motivation. “Let us save what remains: not by vaults and locks which fence them from the public eye and use, in consigning them to the waste of time, but by such a multiplication of copies, as shall place them beyond the reach of accident.”

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Introduction to R/Bioconductor

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  1. Introduction toR/Bioconductor Pieta Schofield Introduction to RR with R

  2. Motivation “Let us save what remains: not by vaults and locks which fence them from the public eye and use, in consigning them to the waste of time, but by such a multiplication of copies, as shall place them beyond the reach of accident.” Thomas Jefferson Introduction to RNA-seq

  3. bioconductor.org Introduction to RNA-seq

  4. Bioconductor • Collection of packages or libraries for R that provide: • Software • Functions to perform certain types of statistical and data analysis tasks • Data structures for holding and manipulation biological data • Annotation Data • Annotation databases • Functions to access and download existing online databases of data and annotations • Experimental Data • Datasets of experimental results Introduction to RNA-seq

  5. Resources • Bioconductor Resources • Course Materials • Support forum • Package vignettes • Common work flows • YouTube Video Channel • Rdocumentation web site for searching for packages from • Comprehensive R Archive Network (CRAN) install.packages() • Bioconductor biocLite() in the BiocInstaller package • Also many packages on GitHub install_github() in the devtools package Introduction to RNA-seq

  6. Bioconductor For NGS There are many Bioconductor packages for RNA-seq • QC (though it is hard to beat FastQC) • ShortRead, EDASeq, htSeqTools... • Alignment • Rsubread, gmapR, Rbowtie.. • Data handling • Biostrings, GenomicRanges, GenomicAlignments, Rsamtools... • Differential Expression • edgeR, DESeq, DESeq2, baySeq, EBSeq, RUVSeq, metaseqR... • Annotation Enrichment Analysis • STRINGdb, gage, topGO, pathview, FGNet... Introduction to RNA-seq

  7. Data Structures • Biostrings: • structures for efficiently holding sequences of amino acids or nucleotides and multiple alignments of sequences. • functions for searching manipulating and pairwise alignment of sequences • GenomicRanges: • structures for holding genomic annotations that occur over 1D regions of sequences • functions for searching, manipulation and calculation with 1D regions • GenomicAlignments: • structures for holding gapped short read alignments • functions for manipulation and calculation over alignments eg. coverage calculation and overlap summation. Introduction to RNA-seq

  8. Practical Go to the practical pages Introduction to RNA-seq

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