Subtrack HOWTO
Contents
How to emulate the UCSC-style subtracks in GBrowse
AKA How to display dense qualitative data in linear tracks that resemble
wiggle tracks
Browser Differences
GBrowse and UCSC differ in how glyphs are organized
- In the UCSC browser, the top-level is track, then subtrack, then
feature/glyph
- In GBrowse, the top-level is track, then feature/glyph. You can have a
mixture of different glyphs in the same track.
How can we make something like a sub-track in gbrowse?
- The use case is a linear “feature” that spans the whole display
window, with all related glyphs (or a single glyph) lined up
horizontally.
- There are a few ways to do this:
Quantitative Wiggle Tracks
- This is an easy one, as quantitative glyphs (like xyplot) already span
the whole chromosome and display in a horizontal line.
- If your data a dense and quantitative, using a wiggle glyph (either
wiggle_xyplot or wiggle_density) will be more efficient
- Each experiment (represented as a single feature/glyph in GBrowse)
looks like a sub-track.
- Some advantages of using WIG vs. GFF are:
There are speed optimizations for both range queries and graphical
rendering.
You also only need one line of GFF in the database for each wiggle_box
track/chromosome.
Non-quantitative Wiggle Tracks
- If you have a large number of scored or non-scored features (> a few
thousand/chromosome) as GFF, they will bog down the database and
probably pile up in a hopeless jumble in the browser.
- You can use the wiggle_box glyph in this situation.
- This is accomplished by converting the GFF to WIG/BED, then loading
the data with the
wiggle2gff3.pl script.
- The wiggle box glyph draws a wiggle track similar to a wiggle density
plot but using a specified color rather than a density gradient.
- It is a good way to handle very dense data that needs to rendered
quickly.
An example of a GFF2WIG(BED) script.
#!/usr/bin/perl -w
use strict;
my $name = shift;
my $desc = shift;
@ARGV or die "I need three args: name, desc, filename";
print qq(track type=wiggle_0 name="$name" description="$desc"\n);
while (<>) {
chomp;
my ($ref,$start,$end,$score) = (split)[0,3,4,5];
$ref =~ s/CHROMOSOME_|chr//;
$start--; # zero-based, half-open
$score = 255 if $score !~ /^[-.Ee0-9]$/;
print join("\t",$ref,$start,$end,$score), "\n";
}
GFF-based, individual features
- If you have a lot of features (lines in the GFF file),
you can load them in the database as individual standalone features,
with no grouping or containment hierarchy, as long as they have an
informative source tag that will allow grouping of the features you
want and exclusion of all others.
- one example would be data that was received in WIG (BED) format but it
would be better suited for GFF.
An example WIG(BED) to GFF3 converter
#!/usr/bin/perl -w
use strict;
@ARGV > 2 or die "use these args: source_tag primary_tag filename\nNOTE primary_tag must be a valid SOFA term!\n";
my $source = shift;
my $type = shift;
for (@ARGV) {
$_ = "sort -k1,1 -k2,2n $_ |";
}
print "##gff-version 3\n";
my $peak_idx = 0;
while (<>) {
chomp;
my ($ref,$start,$end,$score) = split;
$ref =~ /^([IVX]+|MtDNA)$/ or next;
# we will assume that bed lines use the proper zero-based, half open system
$start++;
my $group = "ID=peak".++$peak_idx.";Name=${source}_$peak_idx";
print join("\t",$ref,$source,$type,$start,$end,$score,qw/. ./,$group), "\n";
}
- The source column in GFF is not semantically constrained,
so use an informative tag like TF_binding_DPY27. Then, in the
configuration stanza for the track, use the group on option.
- Also, you can specify a connector between features (default is line)
- Using “group on” is light weight and required less processing of the
GFF.
- Its primary disadvantage is that you can’t get a tidy left-hand label
for the whole track like you can with wiggle tracks.
GFF-based, multi-level features
- If you have a bunch of GFF features but you want them
displayed as anonymous blocks in a single linear feature, reminiscent
of a wiggle_density or wiggle_box glyph (but without the wiggle), do
this:
- Create a parent feature that spans the whole chromosome (one per
chromosome!)
- Make the “real” features sub-parts of the synthetic parent.
Example:
I my_big_thing match 1 15000000 . . . ID=Big_thing_I
I my_little_thing match_part 1 1000 1.234 . . Parent=Big_thing_I;Name="Little_thing_1"
I my_little_thing match_part 5001 6000 0.234 . . Parent=Big_thing_I;Name="Little_thing_1"
I my_little_thing match_part 11000 12000 -2.234 . . Parent=Big_thing_I;Name="Little_thing_1"
etc...
- Now you have just one big feature/chromosome that can look like a
wiggle track, with a tidy left-hand label.
- Note: This approach is only recommended if you have a few hundred
or fewer features/chromosome, as there is some overhead associated
with loading all subparts of each synthetic parent feature.
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