LOST

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

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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? - PowerPoint PPT Presentation

Transcript of LOST

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LOST

Nirav Malani

Rick Bushman LabDepartment of MicrobiologyUniversity of Pennsylvania

in the genome…find where you at,

fool!

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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

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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

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Prepare the Objects> head(sites)

> makeRangedData(sites,soloStart=TRUE)

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Prepare the Objects> head(genes)

> makeRangedData(genes)

Usage: makeRangedData(x, positionsOnly=FALSE, soloStart=FALSE, chromCol=NULL, strandCol=NULL, startCol=NULL, stopCol=NULL)

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Annotation TypesIN/OUT

Usage: getSitesInFeature(sites.rl, genes.rl, “InGene”)

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Annotation TypesIN/OUT

Usage: getSitesInFeature(sites.rl, genes.rl, “InGene”, asBool=T)

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Annotation TypesNEAREST

Usage: getNearestFeature(sites.rl, genes.rl, “NearestGene”)

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Annotation TypesFEATURE COUNTS

Usage: getFeatureCounts( sites.rl, genes.rl, “NumOfGene”,chromSizes = seqlengths(Hsapiens))

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Preliminary Analysis

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Preliminary Analysis

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

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That’s It!