Package 'OGRE'

Title: Calculate, visualize and analyse overlap between genomic regions
Description: OGRE calculates overlap between user defined genomic region datasets. Any regions can be supplied i.e. genes, SNPs, or reads from sequencing experiments. Key numbers help analyse the extend of overlaps which can also be visualized at a genomic level.
Authors: Sven Berres [aut, cre], Jörg Gromoll [ctb], Marius Wöste [ctb], Sarah Sandmann [ctb], Sandra Laurentino [ctb]
Maintainer: Sven Berres <[email protected]>
License: Artistic-2.0
Version: 1.11.0
Built: 2024-11-06 06:37:33 UTC
Source: https://github.com/bioc/OGRE

Help Index

OGRE package to calculate, analyze and visiualize overlap between annotated genomic region datasets

Description

OGRE calculates overlap between user defined annotated genomic region datasets. Any regions can be supplied such as public annotations (genes), genetic variation (SNPs, mutations), regulatory elements (TFBS, promoters, CpG islands) and basically all types of NGS output from sequencing experiments. After overlap calculation, key numbers help analyse the extend of overlaps which can also be visualized at a genomic level.

Details

The main functions are:

OGREDataSetFromDir - build an OGRE dataset from a user defined directory with GRanges annotation files.

  • loadAnnotations - Load dataset files containing genomic regions annotation information from hard drive

OGREDataSet - build an empty OGRE dataset to flexibly add datasets from other sources like AnnotationHub or custom GRanges objects.

fOverlaps - Finds all overlaps between query and subject datasets
sumPlot - calculates key numbers, tables and plots
gvizPlot - generates a genomic plot around query elements with overlapping subject hits.

For additional information, see the package vignette, by typing vignette("OGRE"). Software-related questions or issues can be posted to the Bioconductor Support Site:

https://support.bioconductor.org

or on github:

https://https://github.com/svenbioinf/OGRE

Author(s)

Sven Berres, Jörg Gromoll, Marius Wöste, Sarah Sandmann, Sandra Laurentino

Add dataSet from AnnotationHub

Description

AnnotationHub offers a wide range of annotated datasets which can be manually aquired but need some parsing to work with OGRE as detailed in vignette section "Load datasets from AnnotationHub". For convienence addDataSetFromHub() adds one of the predefined human dataSets of listPredefinedDataSets() to a OGREDataSet.Those are taken from AnnotationHub and are ready to use for OGRE. Additional information on dataSets can be found here listPredefinedDataSets.

Usage

addDataSetFromHub(OGREDataSet, dataSet, type)

Arguments

OGREDataSet

OGREDataSet
dataSet

character Name of one predefined dataSets to add as query or subject to a OGREDataSet. Possible dataSets can be show with listPredefinedDataSets().
type

Type of dataSet, must be either query or subject. If query the dataSet will be added as query and at the first position of OGREDataSet.

Value

OGREDataSet.

Examples

myOGRE <- OGREDataSet() 
myOGRE <- addDataSetFromHub(myOGRE,"protCodingGenes","query")

Add GenomicRanges

Description

Add a GenomicRanges dataset to OGREDataSet

Usage

addGRanges(OGREDataSet, dataSet, type, label = NULL)

Arguments

OGREDataSet

An OGREDataSet
dataSet

A GRanges object. Each region needs chromosome, start, end and strand information. A unique ID and a name column must be present in the GenomicRanges object metadata. Avoid different chromosome naming conventions i.e. (chr1, CHR1, 1, I) among all datasets
type

Type of dataSet, must be either query or subject. If query the dataSet will be added as query and at the first position of OGREDataSet.
label

A character that will label your GRanges object. If not supplied, the label will be guessed from the dataset parameter.

Value

OGREDataSet.

Examples

myOGRE <- OGREDataSet()
myGRanges <- makeExampleGRanges()
myOGRE <- addGRanges(myOGRE,myGRanges,"query")

Coverage plot

Description

Generates coverage plots of all subject datasets and stores them as a list, that can be accessed by metadata(OGREDataSet)$covPlot

Usage

covPlot(
  OGREDataSet,
  datasets = names(OGREDataSet)[seq(2, length(OGREDataSet))],
  nbin = 100
)

Arguments

OGREDataSet

An OGREDataSet
datasets

character vector of subject dataset names. Default: Generates a coverage plots for all subjects
nbin

Number of bins

Value

OGREDataSet.

Examples

myOGRE <- makeExampleOGREDataSet()
myOGRE <- loadAnnotations(myOGRE)
myOGRE <- fOverlaps(myOGRE)
myOGRE <- covPlot(myOGRE)
metadata(myOGRE)$covPlot

Extend a GRanges object

Description

Extend(shrink) ranges of a GRanges object.

Usage

extendGRanges(OGREDataSet, name, upstream = 0, downstream = 0)

Arguments

OGREDataSet

An OGREDataSet
name

character Name of the GRanges object for extending
upstream

int (positive or negative number)
downstream

int (positive or negative number)

Value

OGREDataSet

Examples

myOGRE <- makeExampleOGREDataSet()
myOGRE <- loadAnnotations(myOGRE)
#extend range by shifting start 100 bp in upstream direction
myOGRE <- extendGRanges(myOGRE,"genes",upstream=100)
#shrinking range by shifting end 100 bp in upstream direction
myOGRE <- extendGRanges(myOGRE,"genes",downstream=-100)
#shrinking range by shifting from both sides to the center
myOGRE <- extendGRanges(myOGRE,"genes",upstream=-10,downstream=-10)

Extract promoter

Description

A wrapper of GenomicRanges::promoters() to extract promoter regions of a GRanges object stored in a OGREDataSet

Usage

extractPromoters(OGREDataSet, name, upstream = 2000, downstream = 200)

Arguments

OGREDataSet

An OGREDataSet
name

character Name of the GRanges object
upstream

int (positive) upstream=2000(default)
downstream

int (positive) downstream=200(default)

Value

OGREDataSet

Examples

myOGRE <- makeExampleOGREDataSet()
myOGRE <- loadAnnotations(myOGRE)
myOGRE <- extractPromoters(myOGRE,"genes", upstream=2000, downstream=200)

Find overlaps

Description

Finds all overlaps between query and subject(s) and stores each hit (overlap) in data table detailDT. Data table sumDT shows all overlaps of a certain subject type for all query elements. By default also partially overlaps are reported. Overlap calculation is done using GenomicRanges::findOverlaps() implementation.

Usage

fOverlaps(OGREDataSet, selfHits = FALSE, ignoreStrand = TRUE, ...)

Arguments

OGREDataSet

A OGREDataSet.
selfHits

logical if FALSE(default) ignores self hits of identical regions (with identical IDs) within datasets.
ignoreStrand

logical If TRUE (default) two regions with overlapping locations on different strands are considered an overlap hit.
...

Additional parameters, see GenomicRanges::findOverlaps()

Value

OGREDataSet.

Examples

myOGRE <- makeExampleOGREDataSet()
myOGRE <- loadAnnotations(myOGRE)
myOGRE <- fOverlaps(myOGRE)

Generate Gviz plot

Description

gvizPlot generates a plot around one or many given query elements with all overlapping subject hits. In addition, each generated plot can be stored in the gvizPlots folder get or set by gvizPlotsFolder. A maximum of 25 elements can be plotted per track.

Usage

gvizPlot(
  OGREDataSet,
  query,
  gvizPlotsFolder = metadata(OGREDataSet)$gvizPlotsFolder,
  trackRegionLabels = setNames(rep("ID", length(OGREDataSet)), names(OGREDataSet)),
  trackShapes = setNames(rep("fixedArrow", length(OGREDataSet)), names(OGREDataSet)),
  showPlot = FALSE,
  extendPlot = c(-300, 300),
  nElements = 25
)

Arguments

OGREDataSet

A OGREDataSet.
query

A character vector of one or many query elements ID's (i.e. Gene ID's).
gvizPlotsFolder

A character pointing to the plot(s) output directory. If not supplied a folder is automatically generated and can be accessed by metatdata(OGREDataSet)$gvizPlotsFolder.
trackRegionLabels

A labeled character vector that defines the type of label that is displayed for query and subject elements during plotting. Vector values represent the type of label and vector labels define the type of subject element. In the following example setNames(c("ID","name"),c("genes","CGI")) Value "ID" and label "genes" would annotate your genes with IDs taken from the ID column of your dataset. Datasets not defined in this vector are plotted without track labels.
trackShapes

A labeled character vector that defines the type of shape in which every dataset's elements are displayed. Vector values represent the type of shape and vector labels define the type of subject element. In the following example setNames(c("fixedArrow","box"),c("genes","CGI")) Value "fixedArrow" and label "genes" would display your genes in fixedArrow and CGI as box shape. Possible values: (box, arrow, fixedArrow, ellipse, and smallArrow) Default="fixedArrow"
showPlot

logical If FALSE(default) plots are only saved to gvizPlotsFolder. If TRUE plots are additionally send to the plotting window.
extendPlot

int vector Integer vector of length two that extends the plot window to the left or right by adding the first value to query start and the second value to query end coordinates(bp). e.g. c(-1000,1000) zooms out, c(1000,-1000) zooms in and c(-1000,0) shifts the plot window to the left.
nElements

integer Number of elements that are displayed in each track (Default=25). High n.elements can lead to overplotting. Use nElements=FALSE to display all elements.

Value

OGREDataSet.

Examples

myOGRE <- makeExampleOGREDataSet()
myOGRE <- loadAnnotations(myOGRE)
myOGRE <- fOverlaps(myOGRE)
myOGRE <- gvizPlot(myOGRE,query="ENSG00000142168")

List predefined datasets

Description

Use listPredefinedDataSets() to receive a vector of names for predefined datasets that can be aquired from AnnotationHub that are already correctly parsed and formatted. Each of the listed names can be used as input for addDataSetFromHub(). Currently supported:

  • protCodingGenes - Protein coding genes from HG19 (GRCh37) Ensembl For additional information use: getInfoOnIds(AnnotationHub(), "AH10684")

  • CGI - CpG islands from HG19 UCSC For additional information use: getInfoOnIds(AnnotationHub(), "AH5086")

  • SNP - Common Single Nucleotide Polymorphism from HG19 UCSC For additional information use: getInfoOnIds(AnnotationHub(), "AH5105")

  • TFBS - Transcription Factor Binding Sites conserved from HG19 UCSC For additional information use: getInfoOnIds(AnnotationHub(), "AH5090")

  • Promoters - Promoter and flanking regions from HG19 Ensembl (Note: This annotation is currently not included in AnnotationHub and is therefore downloaded from Ensembl's ftp site)

Usage

listPredefinedDataSets()

Value

character vector.

Examples

listPredefinedDataSets()

Load annotation datasets

Description

Load dataset files containing genomic regions annotation information from hard drive. loadAnnotations calls readQuery and readSubject to read in genomic regions as GenomicRanges objects stored as .RDS / .rds files. Each region needs chromosome, start, end and strand information. A unique ID and a name column must be present in the GenomicRanges object metadata. OGRE searches for the query file in your query folder and any number of subject files in your subjects folder. Alternatively, .gff (v2&v3) files in the query or subject folder with attribute columns containing "ID" and "name" information are read in by OGRE.

Usage

loadAnnotations(OGREDataSet)

Arguments

OGREDataSet

A OGREDataSet.

Value

A OGREDataSet.

Examples

myOGRE <- makeExampleOGREDataSet()
myOGRE <- loadAnnotations(myOGRE)

Make an example GRanges dataset

Description

makeExampleGRanges generates an example GRanges dataset.

Usage

makeExampleGRanges()

Value

OGREDataSet.

Examples

myGRanges <- makeExampleGRanges()

Make a example OGRE dataset

Description

makeExampleOGREDataSet generates a example OGREDataSet from dataset files stored in OGRE's extdata directory.

Usage

makeExampleOGREDataSet()

Value

OGREDataSet.

Examples

myOGRE <- makeExampleOGREDataSet()

BuildOGREDataSet

Description

Builds a OGREDataset as a GenomicRangesList for storing and analysing datasets which can be added by addDataSetFromHub() or addGRanges(). Use BuildOGREDataSetFromDir for adding dataSets stored as files.

Usage

OGREDataSet()

Value

A OGREDataSet.

Examples

myOGRE <- OGREDataSet()

BuildOGREDataSetFromDir

Description

Builds a OGREDataset from user specified directories containing datasets for which an overlap between query and subject is to be calculated. A OGREDataset is a GenomicRangesList which stores datasets in a list like structure and possible metadata information.

Usage

OGREDataSetFromDir(queryFolder, subjectFolder)

Arguments

queryFolder

A character path pointing to the directory where your query dataset is located.
subjectFolder

A character path pointing to the directory where your subject dataset(s) are located.

Value

A OGREDataSet.

Examples

myQueryFolder <- file.path(system.file('extdata', package = 'OGRE'),"query")
mySubjectFolder <- file.path(system.file('extdata', package = 'OGRE'),"subject")
myOGRE <- OGREDataSetFromDir(queryFolder=myQueryFolder,subjectFolder=mySubjectFolder)

Plot histogram

Description

Plots overlap histograms of all subject datasets and stores them as a list, that can be accessed by metadata(myOGRE)$hist

Usage

plotHist(OGREDataSet, plot0 = FALSE)

Arguments

OGREDataSet

An OGREDataSet
plot0

plot0=FALSE(default) plots a histogram of all dataset elements with overlaps, excluding elements without overlaps. plot0=FALSE also includes elements without overlaps.

Value

OGREDataSet.

Examples

myOGRE <- makeExampleOGREDataSet()
myOGRE <- loadAnnotations(myOGRE)
myOGRE <- fOverlaps(myOGRE)
myOGRE <- plotHist(myOGRE)
metadata(myOGRE)$hist

Read dataset(s) from folder

Description

readDataSetFromFolder() scanns queryFolder and subjectFolder for either .RDS/.rds or .CSV/.csv files and adds them to a OGREDataSet. Each region needs chromosome, start, end and strand information. (tabular file columns must be named accordingly). A unique ID and a name column must be present in the GenomicRanges object's metatdata and tabular file.

Usage

readDataSetFromFolder(OGREDataSet, type)

Arguments

OGREDataSet

A OGREDataSet.
type

character and one of query/subject.

Value

A OGREDataSet.

Examples

myOGRE <- makeExampleOGREDataSet()
myOGRE <- readDataSetFromFolder(myOGRE,type="query")
myOGRE <- readDataSetFromFolder(myOGRE,type="subject")

SHREC SHiny interface for REgion Comparison

Description

SHREC() is a graphical user interface for OGRE

Usage

SHREC()

Value

Runs GUI, this function normally does not return

Subset a GRanges object

Description

Subsets a GRanges object with reference to it's ID column using a ID vector.

Usage

subsetGRanges(OGREDataSet, IDs, name)

Arguments

OGREDataSet

An OGREDataSet
IDs

character vector with IDs used to subset the GRanges object defined in name
name

character Name of the GRanges object for subsetting. One of the GRanges objects in a OGREDataSet

Value

OGREDataSet.

Examples

myOGRE <- makeExampleOGREDataSet()
myOGRE <- loadAnnotations(myOGRE)
myOGRE <- subsetGRanges(myOGRE,c("ENSG00000142168","ENSG00000256715"),"genes")

Calculates min/max/average overlap

Description

Calculates min/max/average overlap for all datasets using summary(). Results can be accessed by metadata(OGREDataSet)$summaryDT which is a list() of two data.table objects. The first one includes elements without any overlap at all and the second provides summary numbers for all elements that have at least one overlap.

Usage

summarizeOverlap(OGREDataSet)

Arguments

OGREDataSet

An OGREDataSet

Value

OGREDataSet.

Examples

myOGRE <- makeExampleOGREDataSet()
myOGRE <- loadAnnotations(myOGRE)
myOGRE <- fOverlaps(myOGRE)
myOGRE <- summarizeOverlap(myOGRE)
metadata(myOGRE)$summaryDT

Generate summary plot

Description

sumPlot() calculates key numbers i.e. (total number of overlaps, number of overlaps per subject...) to help with an exploratory data evaluation and displays them in an informative barplot.

Usage

sumPlot(OGREDataSet)

Arguments

OGREDataSet

A OGREDataSet.

Value

OGREDataSet.

Examples

myOGRE <- makeExampleOGREDataSet()
myOGRE <- loadAnnotations(myOGRE)
myOGRE <- fOverlaps(myOGRE)
myOGRE <- sumPlot(myOGRE)