Plotting multiple ranges
-Somtimes it is helpful to plot two non-contiguous genomic ranges side-by-side. This might happen if you’re plotting a structural variant with breakends that are very distant from each other, or even on separate chromosomes. This can be done by supplying multiple ranges as the plotting window as either a GRanges or GRangesList. The following is an example of a plot with discontiguous ranges.
Somtimes it is helpful to plot two non-contiguous genomic ranges
+side-by-side. This might happen if you’re plotting a structural variant
+with breakends that are very distant from each other, or even on
+separate chromosomes. This can be done by supplying multiple ranges as
+the plotting window as either a GRanges or
+GRangesList. The following is an example of a plot with
+discontiguous ranges.
coverage.gr = readRDS(system.file("extdata", "ovcar.subgraph.coverage.rds", package = "gTrack"))
coverage.gt = gTrack(coverage.gr, y.field = "cn", circles = TRUE, lwd.border = 0.2, y0 = 0, y1 = 12)
@@ -111,8 +118,13 @@ Axes and data
Y-coordinates (y.field)
-The x-coordinate of gTrack data is always a genomic interval. The y-coordinate can be either unspecified, or supplied in a metadata column of the GRanges or GRangesList. The name of this metadata column can be specified by supplying a character string to argument for y.field.
-In the following example, we will plot two different metadata fields, one named foreground and one named cn.
+The x-coordinate of gTrack data is always a genomic
+interval. The y-coordinate can be either unspecified, or supplied in a
+metadata column of the GRanges or GRangesList.
+The name of this metadata column can be specified by supplying a
+character string to argument for y.field.
+In the following example, we will plot two different metadata fields,
+one named foreground and one named cn.
coverage.gr = readRDS(system.file("extdata", "ovcar.subgraph.coverage.rds", package = "gTrack"))
@@ -129,7 +141,13 @@ Y-coordinates (y.field)
Track names (name)
-The name specifies the track label that is shown to the right of a subplot. Arguments must be character vectors. The default behavior is to set name to an empty string if y.field is not specified, and otherwise to set name to the value passed to y.field. Below is an example of a scatter plot with and without a name argument.
+The name specifies the track label that is shown to the
+right of a subplot. Arguments must be character vectors. The default
+behavior is to set name to an empty string if
+y.field is not specified, and otherwise to set
+name to the value passed to y.field. Below is
+an example of a scatter plot with and without a name
+argument.
coverage.gr = readRDS(system.file("extdata", "ovcar.subgraph.coverage.rds", package = "gTrack"))
@@ -146,8 +164,12 @@ Track names (name)
Displaying or hiding the Y-axis (yaxis)
-The Y-axis of a gTrack can be toggled on or off entirely using the logical parameter yaxis, which has default value TRUE if y.field is specified and FALSE if not.
-Here is an example where yaxis is deliberately set as FALSE despite suppling a value to y.field.
+The Y-axis of a gTrack can be toggled on or off entirely
+using the logical parameter yaxis, which has default value
+TRUE if y.field is specified and
+FALSE if not.
+Here is an example where yaxis is deliberately set as
+FALSE despite suppling a value to y.field.
coverage.gr = readRDS(system.file("extdata", "ovcar.subgraph.coverage.rds", package = "gTrack"))
@@ -164,7 +186,11 @@ Displaying or hiding the Y-axis (
Quantile-based Y-axis cutoffs (y.quantile)
-By default, the minimum and maximum y-axis values are determined by the values of the 1st and 99th percentiles of the data to be plotted. This percentile can be changed by adjusting y.quantile in order to plot a wider or narrower range of points. The example below compares two different values of y.quantile.
+By default, the minimum and maximum y-axis values are determined by
+the values of the 1st and 99th percentiles of the data to be plotted.
+This percentile can be changed by adjusting y.quantile in
+order to plot a wider or narrower range of points. The example below
+compares two different values of y.quantile.
coverage.gr = readRDS(system.file("extdata", "ovcar.subgraph.coverage.rds", package = "gTrack"))
@@ -181,7 +207,10 @@ Quantile-based Y-axis cutoffs
Specifying Y-axis cutoffs (y0 and y1)
-The minimum and maximum y-axis values can also be specified directly with y0 and y1 respectively, which must be numeric values. Below is an example of the same data with two different settings for y0 and y1.
+The minimum and maximum y-axis values can also be specified directly
+with y0 and y1 respectively, which must be
+numeric values. Below is an example of the same data with two different
+settings for y0 and y1.
coverage.gr = readRDS(system.file("extdata", "ovcar.subgraph.coverage.rds", package = "gTrack"))
@@ -198,7 +227,10 @@ Specifying Y-axis cutoffs (y0 and y
Unbounded Y-axes (y.cap)
-Sometimes we may not want to specify limits on the y-coordinates at all, but rather ensure all points are plotted, regardless of how big or small they may be. This can be done by setting y.cap = FALSE as shown in the following example.
+Sometimes we may not want to specify limits on the y-coordinates at
+all, but rather ensure all points are plotted, regardless of how big or
+small they may be. This can be done by setting
+y.cap = FALSE as shown in the following example.
coverage.gr = readRDS(system.file("extdata", "ovcar.subgraph.coverage.rds", package = "gTrack"))
@@ -219,7 +251,12 @@ Point density and spacing
Stacking adjacent ranges (stack.gap)
-Sometimes closely spaced genomic intervals can be difficult to discern. If no y-coordinate is specified, sometimes it is helpful to stagger these intervals vertically to make them more visually distinct. This can be done by setting the parameter stack.gap to some numeric value. This will vertically stack adjacent intervals separated by a genomic distance (in base pairs) below that value.
+Sometimes closely spaced genomic intervals can be difficult to
+discern. If no y-coordinate is specified, sometimes it is helpful to
+stagger these intervals vertically to make them more visually distinct.
+This can be done by setting the parameter stack.gap to some
+numeric value. This will vertically stack adjacent intervals separated
+by a genomic distance (in base pairs) below that value.
## create tiled genomic intervals
win = GRanges(seqnames = "1", ranges = IRanges(start = 1, width = 1e5))
@@ -237,7 +274,11 @@ Stacking adjacent ranges (stack.gap)
Number of plotted ranges (max.ranges)
-A gTrack with a huge number of genomic intervals can take a long time to plot, and if there are many overlapping points it doesn’t make sense to include all of them. To downsample points, you can set max.ranges to some number, which will only plot that number of randomly selected points.
+A gTrack with a huge number of genomic intervals can
+take a long time to plot, and if there are many overlapping points it
+doesn’t make sense to include all of them. To downsample points, you can
+set max.ranges to some number, which will only plot that
+number of randomly selected points.
coverage.gr = readRDS(system.file("extdata", "ovcar.subgraph.coverage.rds", package = "gTrack"))
@@ -255,7 +296,9 @@ Number of plotted ranges (max.range
Data labels
-By default, named GRanges and GRangesList are labeled in gTrack. This behavior is illustrated in the following example.
+By default, named GRanges and GRangesList
+are labeled in gTrack. This behavior is illustrated in the
+following example.
## define plotting window
win = GRanges(seqnames = "1", ranges = IRanges(start = 1, width = 1e5))
@@ -272,7 +315,10 @@ Data labels
Suppressing labels
-These labels can be hidden by setting labels.suppress to TRUE. If you want to specifically supress labels of a GRanges or GRangesList, you can also use labels.suppress.gr or labels.suppress.grl.
+These labels can be hidden by setting labels.suppress to
+TRUE. If you want to specifically supress labels of a
+GRanges or GRangesList, you can also use
+labels.suppress.gr or labels.suppress.grl.
## create gTrack with no labels
nolabels.gt = gTrack(gr, labels.suppress = TRUE, name = "no labels")
@@ -283,7 +329,12 @@ Suppressing labels
Specifying labels
-Labels can also be specified in a metadata column of a GRanges or GRangesList. To use these labels, the name of the relevant column should be passed as an argument for gr.labelfield or grl.labelfield, as seen in the example below. These will appear in the middle of the GRanges instead of on the left.
+Labels can also be specified in a metadata column of a
+GRanges or GRangesList. To use these labels,
+the name of the relevant column should be passed as an argument for
+gr.labelfield or grl.labelfield, as seen in
+the example below. These will appear in the middle of the GRanges
+instead of on the left.
otherlabels.gt = gTrack(gr, gr.labelfield = "other_labels", name = "other labels", labels.suppress = TRUE)
@@ -297,7 +348,9 @@ Point and line style
Scatterplot point size (lwd.border)
-The size of points in a scatterplot can be controlled by lwd.border with larger values producing larger points. Here is an illustrative example.
+The size of points in a scatterplot can be controlled by
+lwd.border with larger values producing larger points. Here
+is an illustrative example.
coverage.gr = readRDS(system.file("extdata", "ovcar.subgraph.coverage.rds", package = "gTrack"))
@@ -312,7 +365,8 @@ Scatterplot point size (lwd.border)
Width of plotted ranges (ywid)
-The thickness of plotted segments can be adjusted using the ywid parameter.
+The thickness of plotted segments can be adjusted using the
+ywid parameter.
win = GRanges(seqnames = "1", ranges = IRanges(start = 1, width = 1e5))
@@ -325,7 +379,9 @@ Width of plotted ranges (ywid)plot(c(narrow.gt, wide.gt), win)
-Alternatively, by adjusting the ywid metadata column of supplied GRanges, the width of each range can be adjusted individually.
+Alternatively, by adjusting the ywid metadata column of
+supplied GRanges, the width of each range can be adjusted
+individually.
win = GRanges(seqnames = "1", ranges = IRanges(start = 1, width = 1e5))
@@ -345,7 +401,12 @@ Colors
Specifying data color directly (col)
-If col is a metadata column of the GRanges or GRangesList used to construct a gTrack and contains colors (either in hexadecimal form or as character vectors) then these values determine the color of the plotted point. Here is an example, where points within 10 Kbp of a junction breakend are colored in red.
+If col is a metadata column of the GRanges
+or GRangesList used to construct a gTrack and contains
+colors (either in hexadecimal form or as character vectors) then these
+values determine the color of the plotted point. Here is an example,
+where points within 10 Kbp of a junction breakend are colored in
+red.
coverage.gr = readRDS(system.file("extdata", "ovcar.subgraph.coverage.rds", package = "gTrack"))
gg = readRDS(system.file("extdata", "ovcar.subgraph.rds", package = "gTrack"))
@@ -362,7 +423,13 @@ Specifying data color directly (col)
Coloring by secondary label (gr.colorfield and grl.colorfield)
-We can also map discrete values in a metadata column in to colors automatically. Here is one example, using values in near_breakend. Here, gr.colorfield is set to "near_breakend" indicating that the gTrack should color points according to their value in this column. For GRangesList the analogous parameter grl.colorfield should be modified.
+We can also map discrete values in a metadata column in to colors
+automatically. Here is one example, using values in
+near_breakend. Here, gr.colorfield is set to
+"near_breakend" indicating that the gTrack
+should color points according to their value in this column. For
+GRangesList the analogous parameter
+grl.colorfield should be modified.
coverage.col.gt = gTrack(coverage.gr, y.field = "cn", circles = TRUE, lwd.border = 0.2, y0 = 0, y1 = 12, gr.colorfield = "near_breakend")
@@ -373,7 +440,9 @@ Coloring b
Custom map from label to color (colormaps)
-When using gr.colorfield we can also supply a custom map of labels to colors by passing a named vector to colormap. Here is one illustrative example.
+When using gr.colorfield we can also supply a custom map
+of labels to colors by passing a named vector to colormap.
+Here is one illustrative example.
coverage.col.gt = gTrack(coverage.gr, y.field = "cn", circles = TRUE, lwd.border = 0.2, y0 = 0, y1 = 12, gr.colorfield = "near_breakend", colormap = c("yes" = "red", "no" = "blue"))
@@ -384,7 +453,9 @@ Custom map from label to color
Background color (bg.col)
-We can change the background color of our gTrack using the bg.col param. Here is an example where the background is set to blue.
+We can change the background color of our gTrack using the
+bg.col param. Here is an example where the background is
+set to blue.
coverage.col.gt = gTrack(coverage.gr, y.field = "cn", circles = TRUE, lwd.border = 0.2, y0 = 0, y1 = 12, col = "black", bg.col = alpha("blue", 0.1))
@@ -395,7 +466,12 @@ Background color (bg.col)
Color thresholds (cmap.max and cmap.min)
-When plotting matrix and gMatrix heatmaps it is sometimes useful to set thresholds for mapping numerical values to the color gradient. cmap.min is the minimum number, under which the gradient is not applied, and cmap.max is the maximum number to which the gradient is applied. Below, I plot two examples, with different ranges for these parameters.
+When plotting matrix and gMatrix heatmaps
+it is sometimes useful to set thresholds for mapping numerical values to
+the color gradient. cmap.min is the minimum number, under
+which the gradient is not applied, and cmap.max is the
+maximum number to which the gradient is applied. Below, I plot two
+examples, with different ranges for these parameters.
gm = readRDS(system.file("extdata", "ovcar.subgraph.hic.rds", package = "gTrack"))
fp = parse.gr("1:6043576-7172800")
@@ -406,7 +482,12 @@ Color thresholds (cmap.max and c
Legends
-In some of the examples above, you can see that when we use gr.colorfield or grl.colorfield a legend is created to show the mapping of labels to colors. Sometimes, we don’t want to include a legend in our gTrack. Omitting the legend is accomplished by setting the parameter legend to FALSE.
+In some of the examples above, you can see that when we use
+gr.colorfield or grl.colorfield a legend is
+created to show the mapping of labels to colors. Sometimes, we don’t
+want to include a legend in our gTrack. Omitting the legend
+is accomplished by setting the parameter legend to
+FALSE.
coverage.gr = readRDS(system.file("extdata", "ovcar.subgraph.coverage.rds", package = "gTrack"))
gg = readRDS(system.file("extdata", "ovcar.subgraph.rds", package = "gTrack"))
@@ -423,7 +504,11 @@ Legends
Links
-It is possible to plot aberrant adjacencies as a separate track. These must be supplied to the as a GRangesList to the links parameter of plot. The length of each constituent GRanges in this GRangesList should be 2.
+It is possible to plot aberrant adjacencies as a separate track.
+These must be supplied to the as a GRangesList to the
+links parameter of plot. The length of each
+constituent GRanges in this GRangesList should
+be 2.
gg = readRDS(system.file("extdata", "ovcar.subgraph.rds", package = "gTrack"))
## create GRangesList corresponding with ALT edges
@@ -434,7 +519,12 @@ Links
Sequence names with chr prefixes
-Some genome assemblies (e.g. GrCh38) have sequence names with a chr prefix. By default, gTrack strips these prefixes, but sometimes it is preferable to keep them. This can be done by setting chr.sub to FALSE in both plot and gTrack instantiation. An example is below.
+Some genome assemblies (e.g. GrCh38) have sequence names with a
+chr prefix. By default, gTrack strips these
+prefixes, but sometimes it is preferable to keep them. This can be done
+by setting chr.sub to FALSE in both
+plot and gTrack instantiation. An example is
+below.
coverage.new = readRDS(system.file("extdata", "ovcar.subgraph.coverage.chr.rds", package = "gTrack"))
gg.new = readRDS(system.file("extdata", "ovcar.subgraph.chr.rds", package = "gTrack"))
@@ -468,7 +558,7 @@ Sequence names with chr prefixes
-Site built with pkgdown 2.0.6.
+Site built with pkgdown 2.0.7.
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diff --git a/docs/articles/index.html b/docs/articles/index.html
index 698fa07d..792ea643 100644
--- a/docs/articles/index.html
+++ b/docs/articles/index.html
@@ -77,7 +77,7 @@ All vignettes
diff --git a/docs/articles/quickstart.html b/docs/articles/quickstart.html
index b0d1d016..19588819 100644
--- a/docs/articles/quickstart.html
+++ b/docs/articles/quickstart.html
@@ -84,130 +84,215 @@
Creating and plotting gTracks
- Source: ../../../../groups/imielinski_lab/home/zchoo/git/gTrack/vignettes/quickstart.rmd
+ Source: vignettes/quickstart.rmd
quickstart.rmd
-gTrack is a package that enables easy plotting of data across genomic intervals. This is a short tutorial that explains how gTracks can be created and plotted. For this example, we will use a pyrgo locus from the ovarian carcinoma cell line OVCAR-3.
-In general, gTracks can be created from GRanges, GRangesList, and Matrix objects. In addition, we have written a some R packages (gGnome and GxG) in which R6 objects (namely gGraph, gWalk, and gMatrix) include a gTrack constructor (usually invoked by calling the $gt active field or $gtrack method).
+gTrack is a package that enables easy plotting of data
+across genomic intervals. This is a short tutorial that explains how
+gTracks can be created and plotted. For this example, we will use a
+pyrgo locus from the ovarian carcinoma cell line OVCAR-3.
+In general, gTracks can be created from GRanges,
+GRangesList, and Matrix objects. In addition,
+we have written a some R packages (gGnome and GxG) in which R6
+objects (namely gGraph, gWalk, and
+gMatrix) include a gTrack constructor (usually invoked by
+calling the $gt active field or $gtrack
+method).
+
+Setting Up Your Environment
+
+Before proceeding with the tutorial you should first set up your
+environment. gTrack requires version 4.0.2 of R. Versions
+after this will not work. You can download the 4.0.2 pkg
+file (for MacOS) here, or the
+executable (for Windows) here.
+You may also wish to install something like RSwitch to easily switch between
+different R versions you have installed.
+You will also need to install the gGnome
+package:
+
+## allows dependencies that throw warnings to install
+Sys.setenv(R_REMOTES_NO_ERRORS_FROM_WARNINGS = TRUE)
+devtools::install_github("mskilab/gGnome")
+library(gGnome)
+Finally, you’ll need to import gTrack AND
+gUtils:
+
+project_path <- "~/projects/gTrack" ## this should be the path to your gTrack clone
+devtools::load_all(project_path)
+library(gTrack)
+library(gUtils)
+knitr::opts_chunk$set(fig.height = 10)
+
GRanges
-GRanges can be used as the starting point for creating scatter plots, bar plots, and line plots. The x-coordinate of each data point in these plots is specified by the genomic position, while the y-coordinate is stored in a user-defined metadata column of the GRanges object.
-In this example, we will create gTracks to plot read depth in 1 Kbp genomic intervals.
+GRanges can be used as the starting point for creating scatter plots,
+bar plots, and line plots. The x-coordinate of each data
+point in these plots is specified by the genomic position, while the
+y-coordinate is stored in a user-defined metadata column of
+the GRanges object.
+In this example, we will create gTracks to plot read
+depth in 1 Kbp genomic intervals.
Rectangles
-The most basic plot in gTrack will represent each supplied genomic interval as a rectangle. If strand is provided, the verticle edges of the rectangle will be bent in a direction indicating strand (towards the right for + stranded intervals, and towards the left for - stranded intervals. This GRanges contains genomic bins that are all 1 Kbp in width without a strand. However, for the purposes of demonstration, we will also plot some stranded intervals to demonstrate the effect.
-
-coverage.gr = readRDS(system.file("extdata", "ovcar.subgraph.coverage.rds", package = "gTrack"))
+The most basic plot in gTrack will represent each supplied genomic
+interval as a rectangle. If strand is provided, the vertical edges of
+the rectangle will be bent in a direction indicating strand (towards the
+right for + stranded intervals, and towards the left for
+- stranded intervals. This GRanges contains
+genomic bins that are all 1 Kbp in width without a strand. However, for
+the purposes of demonstration, we will also plot some stranded intervals
+to demonstrate the effect.
+
+coverage.gr <- readRDS(system.file("extdata", "ovcar.subgraph.coverage.rds", package = "gTrack"))
## create a plus stranded interval
-plus.coverage.gr = readRDS(system.file("extdata", "ovcar.subgraph.coverage.rds", package = "gTrack"))
-strand(plus.coverage.gr) = "+"
-minus.coverage.gr = readRDS(system.file("extdata", "ovcar.subgraph.coverage.rds", package = "gTrack"))
-strand(minus.coverage.gr) = "-"
+plus.coverage.gr <- readRDS(system.file("extdata", "ovcar.subgraph.coverage.rds", package = "gTrack"))
+strand(plus.coverage.gr) <- "+"
+minus.coverage.gr <- readRDS(system.file("extdata", "ovcar.subgraph.coverage.rds", package = "gTrack"))
+strand(minus.coverage.gr) <- "-"
## create gTracks
-coverage.gt = gTrack(coverage.gr)
-plus.coverage.gt = gTrack(plus.coverage.gr)
-minus.coverage.gt = gTrack(minus.coverage.gr)
-To generate a plot, the plot method is used, which takes two positional arguments, a gTrack and a genomic window over which to generate the plot. The genomic window can be specified as either a GRanges, GRangesList, or a character vector that can be parsed as GRanges. (If window is NULL, then all genomic regions defined in the supplied gTrack will be plotted).
+coverage.gt <- gTrack(coverage.gr)
+plus.coverage.gt <- gTrack(plus.coverage.gr)
+minus.coverage.gt <- gTrack(minus.coverage.gr)
+To generate a plot, the plot method is used, which takes
+two positional arguments, a gTrack and a genomic window
+over which to generate the plot. The genomic window can be specified as
+either a GRanges, GRangesList, or a character
+vector that can be parsed as GRanges. (If
+window is NULL, then all genomic regions
+defined in the supplied gTrack will be plotted).
Here is the original (unstranded) intervals:
-
+
## specify genomic region that will be plotted
-fp = parse.gr("1:6850000-7050000")
+fp <- parse.gr("1:6850000-7050000")
plot(coverage.gt, fp)
-
+
Here is the + stranded intervals:
-
+
## specify genomic region that will be plotted
plot(plus.coverage.gt, fp)
-
+
Here is the - stranded intervals:
-
+
## specify genomic region that will be plotted
plot(minus.coverage.gt, fp)
-
+
Scatter plot
-In this example, we will create a scatter plot. In this GRanges, the (normalized) read depth is contained in a metadata column called cn. We need to specify this column name in the argument y.field when creating our gTrack. To create a scatter plot, we need to set the parameter circles to TRUE. The parameter lwd.border controls the size of the points in the scatter plot, the parameter y0 controls the starting position on the y axis, and the parameter y1 controls the ending position on the y axis.
-
-coverage.gr = readRDS(system.file("extdata", "ovcar.subgraph.coverage.rds", package = "gTrack"))
-coverage.gt = gTrack(coverage.gr, y.field = "cn", circles = TRUE, lwd.border = 0.2, y0 = 0, y1 = 12)
-
+In this example, we will create a scatter plot. In this
+GRanges, the (normalized) read depth is contained in a
+metadata column called cn. We need to specify this column
+name in the argument y.field when creating our gTrack. To
+create a scatter plot, we need to set the parameter circles
+to TRUE. The parameter lwd.border controls the
+size of the points in the scatter plot, the parameter y0
+controls the starting position on the y axis, and the parameter
+y1 controls the ending position on the y axis.
+
+coverage.gr <- readRDS(system.file("extdata", "ovcar.subgraph.coverage.rds", package = "gTrack"))
+coverage.gt <- gTrack(coverage.gr, y.field = "cn", circles = TRUE, lwd.border = 0.2, y0 = 0, y1 = 12)
+
## specify genomic region that will be plotted
-fp = parse.gr("1:6043576-7172800")
+fp <- parse.gr("1:6043576-7172800")
plot(coverage.gt, fp + 1e5)
-
+
Bar plot
-Next, we will plot the same data as a bar plot. To do this, we will set the parameter bars to TRUE.
-
-coverage.bars.gt = gTrack(coverage.gr, y.field = "cn", bars = TRUE, y0 = 0, y1 = 12)
+Next, we will plot the same data as a bar plot. To do this, we will
+set the parameter bars to TRUE.
+
+coverage.bars.gt <- gTrack(coverage.gr, y.field = "cn", bars = TRUE, y0 = 0, y1 = 12)
plot(coverage.bars.gt, fp + 1e5)
-
+
Line plot
-Finally, we will plot these data as a line plot, by setting lines to TRUE.
-
-coverage.lines.gt = gTrack(coverage.gr, y.field = "cn", lines = TRUE, y0 = 0, y1 = 12)
+Finally, we will plot these data as a line plot, by setting
+lines to TRUE.
+
+coverage.lines.gt <- gTrack(coverage.gr, y.field = "cn", lines = TRUE, y0 = 0, y1 = 12)
plot(coverage.lines.gt, fp + 1e5)
-
+
Multiple plots
-A useful feature of gTrack objects is that multiple tracks can be concatenated to produce stacked subplots, as shown in the following example. The direction of concatenation is from the bottom up (so the first gTrack corresponds with the bottom-most subplot and the final gTrack corresponds with the top-most subplot).
-
-concatenated.gt = c(coverage.gt, coverage.bars.gt, coverage.lines.gt)
+A useful feature of gTrack objects is that multiple
+tracks can be concatenated to produce stacked subplots, as shown in the
+following example. The direction of concatenation is from the bottom up
+(so the first gTrack corresponds with the bottom-most
+subplot and the final gTrack corresponds with the top-most
+subplot).
+
+concatenated.gt <- c(coverage.gt, coverage.bars.gt, coverage.lines.gt)
plot(concatenated.gt, fp + 1e5)
-
+
GRangesList
-A gTrack can also be created from a GRangesList. This is desirable when plotting ranges that are grouped together in some way, such as alignments deriving from a single read pair.
+A gTrack can also be created from a
+GRangesList. This is desirable when plotting ranges that
+are grouped together in some way, such as alignments deriving from a
+single read pair.
Unordered GRangesList (default)
-In this example, we will create a gTrack from junction-supporting read pairs. Briefly, these are read pairs that form split, gapped, or discordant alignments, hinting at the existence of a genomic rearrangement.
-The alignments associated with each read pair are represented by a single entry in this example’s GRangesList. In the corresponding gTrack, alignments from the same GRangesList entry are linked together by a light gray horizontal line, making it easy for them to be visually associated.
-You can see that there are many junction-supporting reads associated with read depth change points in the coverage gTrack which makes sense because aberrant adjacencies can produce copy number variants.
-
-reads = readRDS(system.file("extdata", "ovcar.subgraph.reads.rds", package = "gTrack"))
-reads.gt = gTrack(reads)
+In this example, we will create a gTrack from junction-supporting
+read pairs. Briefly, these are read pairs that form split, gapped, or
+discordant alignments, hinting at the existence of a genomic
+rearrangement.
+The alignments associated with each read pair are represented by a
+single entry in this example’s GRangesList. In the
+corresponding gTrack, alignments from the same GRangesList
+entry are linked together by a light gray horizontal line, making it
+easy for them to be visually associated.
+You can see that there are many junction-supporting reads associated
+with read depth change points in the coverage gTrack which
+makes sense because aberrant adjacencies can produce copy number
+variants.
+
+reads <- readRDS(system.file("extdata", "ovcar.subgraph.reads.rds", package = "gTrack"))
+reads.gt <- gTrack(reads)
plot(c(coverage.gt, reads.gt), fp + 1e5)
-
+
Ordered GRangesList (draw.paths)
-Sometimes it is desirable to preserve the ordering of segments within each GRanges in a GRangesList. For instance, if each GRanges represents a rearranged somatic haplotype, it is helpful to visualize the exact order of a rearranged segment. This can be done by setting the parameter draw.paths to TRUE. Notice the difference between the plots when this parameter is set!
-
+Sometimes it is desirable to preserve the ordering of segments within
+each GRanges in a GRangesList. For instance, if each GRanges represents
+a rearranged somatic haplotype, it is helpful to visualize the exact
+order of a rearranged segment. This can be done by setting the parameter
+draw.paths to TRUE. Notice the difference
+between the plots when this parameter is set!
+
## create GRangesList for plotting
-wks.grl = readRDS("~/git/gTrack/inst/extdata/ovcar.subgraph.walks.rds")$grl
-
-fp = parse.gr("1:6043576-7172800")
-paths.gt = gTrack(wks.grl, draw.paths = TRUE, stack.gap = 1e7, name = "paths")
-nopaths.gt = gTrack(wks.grl, draw.paths = FALSE, stack.gap = 1e7, name = "no paths")
+wks.grl <- readRDS(file.path(project_path, "inst/extdata/ovcar.subgraph.walks.rds"))$grl
+fp <- parse.gr("1:6043576-7172800")
+paths.gt <- gTrack(wks.grl, draw.paths = TRUE, stack.gap = 1e7, name = "paths")
+nopaths.gt <- gTrack(wks.grl, draw.paths = FALSE, stack.gap = 1e7, name = "no paths")
plot(c(nopaths.gt, paths.gt), fp + 5e4)
-
+
@@ -216,61 +301,130 @@ Matrices
Heatmaps (mdata)
-A gTrack can be created from a GRanges and a corresponding adjacency matrix in order to plot associations between two genomic ranges. One example of this would be a heatmap, where the color of each cell is proportional to some value defined by its corresponding genomic regions.
-In this example, we will create a heatmap of the number of shared read qnames between pairs of genomic intervals. We will read a GRanges and associated matrix and create a gTrack from these inputs, which we will plot alongside the coverage.
-As you can see, the off-diagonal elements correspond with copy number changep points in the coverage!
-
-mdata.mat = readRDS(system.file("extdata", "ovcar.subgraph.mdata.mat.rds", package = "gTrack"))
-mdata.gr = readRDS(system.file("extdata", "ovcar.subgraph.mdata.gr.rds", package = "gTrack"))
+A gTrack can be created from a GRanges and
+a corresponding adjacency matrix to plot associations between two
+genomic ranges. One example of this would be a heatmap, where the color
+of each cell is proportional to some value defined by its corresponding
+genomic regions.
+In this example, we will create a heatmap of the number of shared
+read qnames between pairs of genomic intervals. We will
+read a GRanges and associated matrix and
+create a gTrack from these inputs, which we will plot
+alongside the coverage.
+As you can see, the off-diagonal elements correspond with copy number
+change points in the coverage!
+
+mdata.mat <- readRDS(system.file("extdata", "ovcar.subgraph.mdata.mat.rds", package = "gTrack"))
+mdata.gr <- readRDS(system.file("extdata", "ovcar.subgraph.mdata.gr.rds", package = "gTrack"))
-heatmap.gt = gTrack(mdata.gr, mdata = mdata.mat, cmap.max = 10)
+heatmap.gt <- gTrack(mdata.gr, mdata = mdata.mat, cmap.max = 10)
plot(c(coverage.gt, heatmap.gt), fp + 1e5)
-
+
Connections (edges)
-Instead of a heatmap, it is also possible to plot the edges between genomic intervals by supplying an adjacency list. In this next example, we will plot edges associated with the off-diagonal squares in the previous heatmap.
-
-edges.dat = readRDS(system.file("extdata", "ovcar.subgraph.edges.dat.rds", package = "gTrack"))
-edges.gr = readRDS(system.file("extdata", "ovcar.subgraph.edges.gr.rds", package = "gTrack"))
+Instead of a heatmap, it is also possible to plot the edges between
+genomic intervals by supplying an adjacency list. In this next example,
+we will plot edges associated with the off-diagonal squares in the
+previous heatmap.
+
+edges.dat <- readRDS(system.file("extdata", "ovcar.subgraph.edges.dat.rds", package = "gTrack"))
+edges.gr <- readRDS(system.file("extdata", "ovcar.subgraph.edges.gr.rds", package = "gTrack"))
-edges.gt = gTrack(edges.gr, edges = edges.dat)
+edges.gt <- gTrack(edges.gr, edges = edges.dat)
plot(c(coverage.gt, edges.gt), fp + 1e5)
-
+
gGraph
-gGraphs are genome graphs in which nodes represent (signed) genomic intervals, and edges represent adjacencies between those intervals (see our gGnome package here!).
-A gTrack can be created from a gGraph using either the $gt active field or $gtrack method, as shown below. In this example, we will create a plot of a tumor gGraph and the associated coverage profile.
-
-gg = readRDS(system.file("extdata", "ovcar.subgraph.rds", package = "gTrack"))
+gGraphs are genome graphs in which nodes represent
+(signed) genomic intervals, and edges represent adjacencies between
+those intervals (see our gGnome package here!).
+A gTrack can be created from a gGraph using
+either the $gt active field or $gtrack method,
+as shown below. In this example, we will create a plot of a tumor
+gGraph and the associated coverage profile.
+
+gg <- readRDS(system.file("extdata", "ovcar.subgraph.rds", package = "gTrack"))
plot(c(coverage.gt, gg$gt), fp + 1e5)
-
+
gWalk
-gWalks represent paths through a gGraph. Generally, they represent somatic haplotypes that could exist in a genome corresponding with a give gGraph (more details in the gGnome package!). Like gGraphs, gWalks have active field $gt and method $gtrack, both of which will produce a gTrack.
-The following example plots a set of gWalks associated with the gGraph plotted above.
-
-wks = readRDS(system.file("extdata", "ovcar.subgraph.walks.rds", package = "gTrack"))
+gWalks represent paths through a gGraph.
+Generally, they represent somatic haplotypes that could exist in a
+genome corresponding with a given gGraph (more details in
+the gGnome package!). Like gGraphs,
+gWalks have active field $gt and method
+$gtrack, both of which will produce a
+gTrack.
+The following example plots a set of gWalks associated
+with the gGraph plotted above.
+
+wks <- readRDS(system.file("extdata", "ovcar.subgraph.walks.rds", package = "gTrack"))
plot(c(coverage.gt, gg$gt, wks$gt), fp + 1e5)
-
+
gMatrix
-gMatrix is an object implemented in the package GxG that facilitates analysis and visualization of paired genomic intervals. There are many use cases for gMatrix, but the one used in this example is Hi-C data, which consists of read counts shared by pairs of genomic bins. We will plot the Hi-C profile associated with this locus.
-Again, similar to gWalk and gGraph, a gTrack can be created for a gMatrix with the active field $gt or method $gtrack. Here we will use the $gtrack method to set a parameter for coloring the heatmap (cmap.max).
-
-gm = readRDS(system.file("extdata", "ovcar.subgraph.hic.rds", package = "gTrack"))
+gMatrix is an object implemented in the package
+GxG that facilitates analysis and visualization of paired
+genomic intervals. There are many use cases for gMatrix,
+but the one used in this example is Hi-C data, which consists of read
+counts shared by pairs of genomic bins. We will plot the Hi-C profile
+associated with this locus.
+Again, similar to gWalk and gGraph, a
+gTrack can be created for a gMatrix with the
+active field $gt or method $gtrack. Here we
+will use the $gtrack method to set a parameter for coloring
+the heatmap (cmap.max).
+
+gm <- readRDS(system.file("extdata", "ovcar.subgraph.hic.rds", package = "gTrack"))
plot(c(coverage.gt, gg$gt, gm$gtrack(cmap.max = 1000)), fp + 1e5)
-
+
+
+
+Karyogram
+
+You can plot karyograms in gTrack. If no file is passed to the
+karyogram method as an argument, it will use the karyogram
+datafiles (hg18 or hg19, depending on if the hg19 parameter
+is set to FALSE) included with the package. You can specify
+if you colored giemsa bands by setting the bands parameter
+to TRUE or FALSE (enabled by default). You can
+also return the chromosome arms with different colors, and with
+centromeres and telemeres marked, by setting arms = TRUE
+(also enabled by default)
+Here we are plotting the default assembly, hg18, with the bands and
+arms.
+
+karyogram_fp <- parse.gr("1:1-200000000")
+karyogram_gt_hg18 <- karyogram(hg19 = FALSE)
+plot(karyogram_gt_hg18, karyogram_fp)
+
+
+
+Gencode Tracks
+
+gTrack can also plot a gencode gene track using the
+track.gencode method. This method will download the
+specified build (indicated by the build parameter) from mskilab.com. You can filter genes by supplying a
+character vector to the grep parameter, the
+grepe parameter (to exclude genes), or the
+genes paramter (to limit the gTrack to only those
+genes).
+
+gencode_fp <- parse.gr("1:6000000-6000100")
+gencode_gt <- track.gencode(grep = "NPH", grepe = "S2")
+expect_error(plot(gencode_gt, gencode_fp + 1e5), NA)
+
@@ -291,7 +445,7 @@ gMatrix
-Site built with pkgdown 2.0.6.
+Site built with pkgdown 2.0.7.
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diff --git a/docs/authors.html b/docs/authors.html
index de377448..bae41dc9 100644
--- a/docs/authors.html
+++ b/docs/authors.html
@@ -32,6 +32,9 @@
@@ -99,7 +102,7 @@ Citation
diff --git a/docs/index.html b/docs/index.html
index d9e8d556..5dbba87d 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -53,6 +53,9 @@
@@ -90,21 +93,27 @@
Installation
-## allows dependencies that throw warnings to install
-Sys.setenv(R_REMOTES_NO_ERRORS_FROM_WARNINGS = TRUE)
-
-## install with devtools
-devtools::install_github('mskilab/gTrack)
-See documentation
-
+
+## allows dependencies that throw warnings to install
+Sys.setenv(R_REMOTES_NO_ERRORS_FROM_WARNINGS = TRUE)
+
+## install with devtools
+devtools::install_github('mskilab-org/gTrack')
+See documentation Quickstart Read the docs R Documentation
+
+
-
Attributions
-Marcin Imielinski - Assistant Professor, Weill-Cornell Medical College. Developed while a fellow in the Matthew Meyerson Lab, Dana Farber Cancer Institute, Broad Institute
-Jeremiah Wala - Harvard MD-PhD candidate, Bioinformatics and Integrative Genomics, Rameen Beroukhim Lab, Dana Farber Cancer Institute
+
+Marcin Imielinski - Assistant Professor, Weill-Cornell Medical College. Developed while a fellow in the Matthew Meyerson Lab, Dana Farber Cancer Institute, Broad Institute
+
+
+Jeremiah Wala - Harvard MD-PhD candidate, Bioinformatics and Integrative Genomics, Rameen Beroukhim Lab, Dana Farber Cancer Institute
+
@@ -162,7 +171,7 @@ Dev status
diff --git a/docs/news/index.html b/docs/news/index.html
index 8c9fb3a1..0ea21a68 100644
--- a/docs/news/index.html
+++ b/docs/news/index.html
@@ -32,6 +32,9 @@
@@ -58,8 +61,9 @@ Changelog
+gTrack 0.1.0 2016-3-18
+- Initial stable release to Github
+
diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml
index 642f8acd..41848caf 100644
--- a/docs/pkgdown.yml
+++ b/docs/pkgdown.yml
@@ -1,8 +1,8 @@
-pandoc: 2.2.3.2
-pkgdown: 2.0.6
+pandoc: 3.1.3
+pkgdown: 2.0.7
pkgdown_sha: ~
articles:
- quickstart: quickstart.html
gtrackparams: gtrackparams.html
-last_built: 2023-05-16T18:31Z
+ quickstart: quickstart.html
+last_built: 2023-06-15T18:30Z
diff --git a/docs/reference/affine-map-methods.html b/docs/reference/affine-map-methods.html
index a0de3d93..78cb2ee6 100644
--- a/docs/reference/affine-map-methods.html
+++ b/docs/reference/affine-map-methods.html
@@ -32,6 +32,19 @@
diff --git a/docs/reference/alpha.html b/docs/reference/alpha.html
index a8199d64..6e2a5083 100644
--- a/docs/reference/alpha.html
+++ b/docs/reference/alpha.html
@@ -26,6 +26,19 @@
diff --git a/docs/reference/barbs.html b/docs/reference/barbs.html
index 851023c5..ddc62294 100644
--- a/docs/reference/barbs.html
+++ b/docs/reference/barbs.html
@@ -32,6 +32,19 @@
diff --git a/docs/reference/bernsteinp.html b/docs/reference/bernsteinp.html
index 7f37bc02..ddf3e868 100644
--- a/docs/reference/bernsteinp.html
+++ b/docs/reference/bernsteinp.html
@@ -31,6 +31,19 @@
diff --git a/docs/reference/blend.html b/docs/reference/blend.html
index 595388cc..b6b30a0c 100644
--- a/docs/reference/blend.html
+++ b/docs/reference/blend.html
@@ -25,6 +25,19 @@
diff --git a/docs/reference/brewer.master.html b/docs/reference/brewer.master.html
index 50a61203..9d1b69ef 100644
--- a/docs/reference/brewer.master.html
+++ b/docs/reference/brewer.master.html
@@ -26,6 +26,19 @@
diff --git a/docs/reference/c-methods.html b/docs/reference/c-methods.html
index 88d76e2f..21f8c5f8 100644
--- a/docs/reference/c-methods.html
+++ b/docs/reference/c-methods.html
@@ -26,6 +26,19 @@
diff --git a/docs/reference/cash-methods.html b/docs/reference/cash-methods.html
index 814a8229..7872f926 100644
--- a/docs/reference/cash-methods.html
+++ b/docs/reference/cash-methods.html
@@ -25,6 +25,19 @@
diff --git a/docs/reference/cash-set-methods.html b/docs/reference/cash-set-methods.html
index 115043a6..c549b0bf 100644
--- a/docs/reference/cash-set-methods.html
+++ b/docs/reference/cash-set-methods.html
@@ -29,6 +29,19 @@
diff --git a/docs/reference/clear-methods.html b/docs/reference/clear-methods.html
index 516ee68d..910b3db4 100644
--- a/docs/reference/clear-methods.html
+++ b/docs/reference/clear-methods.html
@@ -27,6 +27,19 @@
diff --git a/docs/reference/clip_polys.html b/docs/reference/clip_polys.html
index caf8e915..6e2a96f2 100644
--- a/docs/reference/clip_polys.html
+++ b/docs/reference/clip_polys.html
@@ -25,6 +25,19 @@
diff --git a/docs/reference/col.scale.html b/docs/reference/col.scale.html
index 554f28e0..6c15ddf4 100644
--- a/docs/reference/col.scale.html
+++ b/docs/reference/col.scale.html
@@ -29,6 +29,19 @@
diff --git a/docs/reference/color.bar.html b/docs/reference/color.bar.html
index 50764086..4f81b645 100644
--- a/docs/reference/color.bar.html
+++ b/docs/reference/color.bar.html
@@ -28,6 +28,19 @@
diff --git a/docs/reference/colormap-methods.html b/docs/reference/colormap-methods.html
index 26f2f3cf..109b7bc5 100644
--- a/docs/reference/colormap-methods.html
+++ b/docs/reference/colormap-methods.html
@@ -29,6 +29,19 @@
diff --git a/docs/reference/colormap-set-methods.html b/docs/reference/colormap-set-methods.html
index a144858a..5732a1b4 100644
--- a/docs/reference/colormap-set-methods.html
+++ b/docs/reference/colormap-set-methods.html
@@ -29,6 +29,19 @@
diff --git a/docs/reference/connectors.html b/docs/reference/connectors.html
index 6d0e4f06..81f6c94c 100644
--- a/docs/reference/connectors.html
+++ b/docs/reference/connectors.html
@@ -40,6 +40,19 @@
diff --git a/docs/reference/dat-methods.html b/docs/reference/dat-methods.html
index 9b57b39c..fc67a90f 100644
--- a/docs/reference/dat-methods.html
+++ b/docs/reference/dat-methods.html
@@ -28,6 +28,19 @@