Examples¶
Synchronizing location, zoom and value scales¶
To synchronize, the locations, zoom levels and value scales, use the provided
location_syncs
, zoom_syncs
and value_scale_syncs
parameters of
the of the display
function.
The location_syncs
and zoom_syncs
parameters both take a list of lists
of views which will have their location and / or zoom synchronized. While the
HiGlass implementation allows for synching of location and zoom independently
at a given offset, the Python API currently only allows synchronization at
the same location and / or same zoom level. It is highly recommended that the
zoom and location syncs are both provided and identical to ensure that zoom
and location change together in the provided list of views.
from higlass.client import View, Track
import higlass
t1 = Track(track_type='top-axis', position='top')
t2 = Track(track_type='heatmap', position='center',
tileset_uuid='CQMd6V_cRw6iCI_-Unl3PQ',
server="http://higlass.io/api/v1/")
# the entire viewport has a width of 12 so a width of 6 for
# each view means they take up half the width
view1 = View([t1, t2], width=6)
view2 = View([t1, t2], width=6, x=6)
display, server, viewconf = higlass.display(
[view1, view2],
location_syncs = [[view1, view2]],
zoom_syncs = [[view1, view2]],
value_scale_syncs = [[(view1, t2), (view2, t2)]])
display
BAM Files¶
View sequencing read mappings.
import higlass
from higlass.tilesets import Tileset, bam
from higlass.client import Track, View
filename = '../data/ont.10K.bam'
indexfile = '../data/ont.10K.bam.bai'
bam_ts = bam(filename, indexfile)
display, server, viewconf = higlass.display(
[View([
Track('top-axis', height=20),
Track(track_type="pileup",
position='top', tileset=bam_ts, height=50 )
], initialXDomain = [
0,
2000
])]
)
display

Multivec Files¶
To view multivec files, we have to load the higlass plugin track. Execute the following code in a cell in the Jupyter notebook you’re using.
%%javascript
require(["https://unpkg.com/higlass-multivec/dist/higlass-multivec"],
function(hglib) {
});
Create the multivec and output file:
from clodius.multivec import create_multivec_multires
output_file = "/Users/pete/tmp/my_file.multires.hdf5"
create_multivec_multires(
array,
[('chr1', chrom_len)],
agg=lambda x: np.nansum(x.T.reshape((x.shape[1], -1, 2)), axis=2).T,
starting_resolution=1,
row_infos = ["match", 'a', 'g', 't'],
output_file=output_file,
tile_size=256
)
ts = multivec(output_file)
Create the viewer:
import higlass
from higlass.client import Track, View
display, server, viewconf = higlass.display(
[View([
Track('top-axis', height=20),
Track(track_type="horizontal-stacked-bar", position='top', tileset=ts, height=50 )
], initialXDomain = [
0,
1000000
])]
)
display