A common task in bioinformatics is to create visualization of genomic data along genomic coordinates, together with necessary genomic annotation features like genes and transcripts on the same coordinate, in order to make sense of those data.
Typically, this can be accomplished with a browser-based genome browser like UCSC genome browser or IGV, which requires to export the data from R. There are also R packages developed to address this issue but using static graphs, e.g.
While bioconductor have packages that excel at representing and analyzing such genomic data, there lacks a flexible and interactive way to view them. Sometimes there is no need for a full-functional genome browser but a fast and convenient way to view the data which are typically represented by a R object. It should also be interactive to aid exploration, for example it may be dragable and it may enable tooltips to get detailed information about a separate feature quickly.
TnT is a new package, any feedback or suggestion would appreciated, please email to Jialin Ma < firstname.lastname@example.org >. You can also find the source repository at https://github.com/marlin-na/TnT and the documentation site at http://tnt.marlin.pub . This vignette will also be extended in the future to include more details.
You can install the stable version of TnT from Bioconductor:
Or alternatively, install the devel version from github:
Then attach the package.
This vignette will assume readers have experience with common data structures in bioconductor, especially
GRanges class from
Overall, the package works by constructing tracks from data (GRanges, TxDb, EnsDb, etc.), and then constructing a tnt board from a list of tracks.
So the first step is to choose a track constructor and use it to construct tracks from data. Different constructors have been provided by the package for different features and data types.
As a simple example, to construct a block track from GRanges object
gr <- GenomicRanges::GRanges("chr7", ranges = IRanges( start = c(26549019L, 26564119L, 26585667L, 26591772L, 26594192L, 26623835L, 26659284L, 26721294L, 26821518L, 26991322L), end = c(26550183L, 26564500L, 26586158L, 26593309L, 26594570L, 26624150L, 26660352L, 26721717L, 26823297L, 26991841L)), ID = 1:10, Name = paste("My Range", 1:10) ) btrack <- TnT::BlockTrack(gr) btrack
## A BlockTrack ## | Label: gr ## | Background: missing, use 'white' ## | Height: 30 ## | Data: ## | seqnames start end width strand tooltip.ID tooltip.Name ## | <factor> <integer> <integer> <integer> <factor> <integer> <character> ## | 1 chr7 26549019 26550183 1165 * 1 My Range 1 ## | 2 chr7 26564119 26564500 382 * 2 My Range 2 ## | 3 chr7 26585667 26586158 492 * 3 My Range 3 ## | 4 chr7 26591772 26593309 1538 * 4 My Range 4 ## | 5 chr7 26594192 26594570 379 * 5 My Range 5 ## | 6 chr7 26623835 26624150 316 * 6 My Range 6 ## | 7 chr7 26659284 26660352 1069 * 7 My Range 7 ## | 8 chr7 26721294 26721717 424 * 8 My Range 8 ## | 9 chr7 26821518 26823297 1780 * 9 My Range 9 ## | 10 chr7 26991322 26991841 520 * 10 My Range 10 ## | color key ## | <character> <integer> ## | 1 blue 1 ## | 2 blue 2 ## | 3 blue 3 ## | 4 blue 4 ## | 5 blue 5 ## | 6 blue 6 ## | 7 blue 7 ## | 8 blue 8 ## | 9 blue 9 ## | 10 blue 10
As you can see, meta-columns of GRanges have been converted to the tooltip column in track data. This is the default argument behavior, see
## function (range, label = deparse(substitute(range)), tooltip = mcols(range), ## color = "blue", background = NULL, height = 30) ## NULL
tooltip can be given as a data frame parallel to the data, the
color argument can also be a character vector parallel to the data setting colors for each individual range.
In order to view track, simply put that track into a TnTBoard/TnTGenome:
## - Missing argument `view.range`: ## automatically select 26493666..27047193 on seqlevel chr7...
## - Missing argument `coord.range` and seqlength is unknown: ## automatically set coordinate limit to 26454128..27086731 ...
You can drag to move, scroll to zoom and click on feature to see the tooltip.
Similarly, tracks of different features could be constructed with other constructors. Here is a table showing these constructors and their data sources. Links to examples of each track type are also provided and you are recommended to go through them.
|VlineTrack||Width-one GRanges||vline||Vline Track|
|PinTrack||Width-one GRanges paired with values||pin||Pin Track|
|LineTrack||Width-one GRanges paired with values||line||Line and Area Track|
|AreaTrack||Width-one GRanges paired with values||area||Line and Area Track|
|GeneTrackFromTxDb||TxDb||gene||Gene Track and Feature Track|
|FeatureTrack||GRanges||gene||Gene Track and Feature Track|
|GroupFeatureTrack||GRangesList||tx||Tx Track and GroupFeatureTrack|
|TxTrackFromTxDb||TxDb||tx||Tx Track and GroupFeatureTrack|
|TxTrackFromGRanges||GRanges paired with ‘type’ and ‘tx_id’||tx||Tx Track and GroupFeatureTrack|
|merge||Two or more tracks||composite||Composite Track|
It is worthwhile to mention CompositeTrack here: you can
merge multiple tracks to construct a CompositeTrack so that different types of features can be shown within one track. See example here.
Given a constructed track, we may want to access or modify its data and options.
There are three common options for all types of tracks, they are
label. These three options can be accessed and modified via
trackSpec<-. For example:
Data of tracks are normally stored with a class that inherits
GRanges (except CompositeTrack, in which the data is stored as a list of tracks), and can be accessed or modified via
trackData<-. There are also convenience shortcuts
track$name <- value for
trackData(track)$name <- value, respectively. As an example:
##  "blue" "blue" "blue" "blue" "blue" "blue" "blue" "blue" "blue" "blue"
As an example, let’s also modify the data:
Finally, we put the modified track and the original track together to see the difference.
## - Missing argument `view.range`: ## automatically select 26504916..27045943 on seqlevel chr7...
## - Missing argument `coord.range` and seqlength is unknown: ## automatically set coordinate limit to 26451985..27098874 ...
Another thing we may want to modify is tooltip. By constructing the track via constructors (except those constructed from TxDb), tooltip can be given as a data frame parallel to the data. After the track is constructed, the tooltip can accessed via
tooltip(track) which is an shortcut to
trackData(track)$tooltip. For example:
## - Missing argument `coord.range` and seqlength is unknown: ## automatically set coordinate limit to 26464128..27096731 ...
Try to click on the block to see the tooltip.
In previous examples, we have already seen how to show tracks with a TnTBoard or TnTGenome. A TnTBoard stores a list of tracks and show them with the same coordinate. You may already have noticed the difference between TnTBoard and TnTGenome: TnTGenome is just a TnTBoard with axis and location label.
In this part, I will introduce some arguments that can be optionally provided to control the board. They are:
view.range: GRanges, to set the initial view range.
coord.range: IRanges or numeric, to set the cooordinate limit.
zoom.allow: IRanges or numeric, to set the limit of extent when zooming in and out.
allow.drag: Logical, if FALSE, the board will not be able to move or zoom.
In case that
zoom.allow not provided, TnT will take a guess on them. Some considerations are:
view.range: Try to use the seqlevel on which all tracks have features and try to use intersection of ranges of all tracks.
seqinfoof the tracks have
seqlengthsavailable, then use 1 to seqlength as coordinate range. If not, try to find based on ranges of features (i.e. to cover all features on that seqlevel).
An example using these arguments:
set.seed(6) pintrack <- TnT::PinTrack(GRanges("chr7", IRanges(start = sample(26300000:27000000, 4), width = 1)), value = c(1,3,2,4), color = c("blue", "yellow", "green", "red")) TnT::TnTGenome( list(pintrack, btrack2), view.range = GRanges("chr7", IRanges(26550000, 26600000)), coord.range = IRanges(26350000, 27050000), zoom.allow = IRanges(50000, 200000) )