Visualise NGS Data Tracks

Federico Agostini

Getting Started

These instructions will get you a copy of the project up and running on your local machine for usage, development or testing purposes. See deployment for notes on how to deploy the project on a live system.

Prerequisities

A pre-installed version of R (>= 3.4.3), which can be downloaded from here or here.

Install from source

The aim of devtools is to make your life as a package developer easier by providing R functions that simplify many common tasks. devtools is opinionated about how to do package development, and requires that you use roxygen2 for documentation:

require(devtools)
require(roxygen2)

Converts roxygen comments to .Rd files

roxygenise()

Builds a package file from package sources

build()

[Optional] Updates the documentation, then builds and checks the package

check()

Reinstalls the package, detaches the currently loaded version then reloads the new version with library().

install()

Install from repository

Install the devtools package and load it

install.packages("devtools")
library(devtools)

[Option 1] Use install_github("author/package"). For example, with this fagostini/Kvasir package, which exists at github.com/fagostini/Kvasir

install_github("fagostini/Kvasir")
library(Kvasir)

[Option 2] Use install.packages()

install.packages(path_to_file, repos = NULL, type="source")

There's some extra fanciness that you need to do if the version you want sits on some branch of the repository, if the package is in a subdirectory of the main repository, or if the package is a private repository.

For example, to install a private repository you should provide the install_github() with your authentication credentials.

install_github("fagostini/Kvasir", auth_user=username, password=password)

To-Do

• Merge annotation and data tracks (presently, the user has to merge the plots)
• Add the option for differential track colours/fills
• Improve the annotation (e.g. mark UTRs and coding/non-coding genes)

---

Case study

Human HNRNPC binding to a region on chromosomes 14.

Setup

require("ggplot2")
require("cowplot")
require("ggthemes")
require("data.table")
require("GenomicFeatures")
require("rtracklayer")
require("zoo")

require("Kvasir")

## Warning: replacing previous import 'cowplot::theme_map' by 'ggthemes::theme_map'
## when loading 'Kvasir'

species = "Homo sapiens" # or 'Mus musculus' for mouse
genome = "hg19" # or hg38 or mm10 for mouse
version = "19" # or 27 or M14 for mouse

If any of the information above does not suit your needs, please review it in the 'setup' chunk.

Gencode Annotation (GFF3)

If it not not present in the working folder, the pipeline will download the Comprehensive gene annotation from Gencode and create a local database.

if( require("TxDb.Hsapiens.UCSC.hg19.knownGene") ){
   TxDb = TxDb.Hsapiens.UCSC.hg19.knownGene
}else{
   TxDb = getTxDb(species, genome, version)
}

Annotation track

Genic and exonic features are extracted from the database, ranked by size (larger on top) and distributed over different levels to prevent overlaps.

region = GRanges("chr14", IRanges(50027696, 50277302))

anno.pl = createAnnoTrack(TxDb, region, min.unit=width(region)/100, species)

## Check the annotation...

## Extract features...

## Apply layering...

## Create track data...

## Loading required package: org.Hs.eg.db

## 

## 'select()' returned 1:1 mapping between keys and columns

## Done

region.pl = as.data.table(region)

pl = plotAnno(anno.pl, range(region.pl[, list(start, end)]), addID=TRUE)

require("GenomicAlignments")
require("RNAseqData.HNRNPC.bam.chr14")

bamfiles = RNAseqData.HNRNPC.bam.chr14_BAMFILES[1:2]
param = ScanBamParam(tag="NM")
galp = lapply(bamfiles, function(x) suppressWarnings(readGAlignmentPairs(x, use.names=TRUE, param=param)))

ggl = createTracks(galp, region=region, use.smooth=FALSE)

ggl = plot_grid(plotlist=c(ggl, list(pl)), nrow=length(ggl)+1, axis="lr", align="v", rel_heights=c(rep((1-0.25)/length(ggl), length(ggl)), 0.25))