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