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LOST

LOST. in the genome… f ind where you at, fool!. Nirav Malani Rick Bushman Lab Department of Microbiology University of Pennsylvania. Basic Idea: “ Know Your Surroundings”. Where is the concept coming from? Retrovirus integration pattern What are you trying to deduce?

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LOST

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  1. LOST in the genome… find where you at, fool! Nirav Malani Rick Bushman Lab Department of Microbiology University of Pennsylvania

  2. Basic Idea:“Know Your Surroundings” • Where is the concept coming from? • Retrovirus integration pattern • What are you trying to deduce? • Sense of genomic environment and/or preferences • What kind of data are you analyzing? • Genomic coordinates from some species

  3. hiAnnotator • R package to annotate genomic ranges • Fundamentals • Take two RangedData objects (query & subject) • Call a specific annotation type function • Define customization parameters…optional. • That’s it! • Depends On: IRanges, doBy

  4. Prepare the Objects > head(sites) > makeRangedData(sites,soloStart=TRUE)

  5. Prepare the Objects > head(genes) > makeRangedData(genes) Usage: makeRangedData(x, positionsOnly=FALSE, soloStart=FALSE, chromCol=NULL, strandCol=NULL, startCol=NULL, stopCol=NULL)

  6. Annotation Types In/Out Usage: getSitesInFeature(sites.rl, genes.rl, “InGene”)

  7. Annotation Types In/Out Usage: getSitesInFeature(sites.rl, genes.rl, “InGene”, asBool=T)

  8. Annotation Types Nearest Usage: getNearestFeature(sites.rl, genes.rl, “NearestGene”)

  9. Annotation Types Feature Counts • Usage: getFeatureCounts( sites.rl, genes.rl, “NumOfGene”, • chromSizes= seqlengths(Hsapiens))

  10. Preliminary Analysis

  11. Preliminary Analysis

  12. In Works • Parallel backend support for all the functions • Function for GC% annotation

  13. That’s It!

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