Local Data¶
Warning
This feature is only available in local environments and not for remove systems (like Colab or MyBinder).
Data sources for the Gosling specification are expected to be accessible via HTTP. Loading a local dataset can be challenging since it requires starting a web-server and/or a Higlass server for some pre-aggregated datasets.
The data utilities in gos will transparently serve data via a background ASGI server if a local file path is detected.
import gosling as gos
# gos.bam, gos.csv, gos.bigwig # file resources
# gos.beddb, gos.vector, gos.matrix, gos.multivec # higlass tile resources
Installation¶
You will need to install Clodius for any higlass tile resources:
pip install clodius # optional, required for higlass tile resources
Usage¶
The gos example below incudes a multivec data source; the url points to a Higlass server endpoint for the corresponding tileset information.
import gosling as gos
data = gos.multivec(
url="https://server.gosling-lang.org/api/v1/tileset_info/?d=cistrome-multivec",
row="sample",
column="position",
value="peak",
categories=["sample 1", "sample 2", "sample 3", "sample 4"],
binSize=5,
)
track = gos.Track(data).mark_rect().encode(
x=gos.X("start:G", axis="top"),
xe="end:G",
row=gos.Row("sample:N", legend=True),
color=gos.Color("peak:Q", legend=True),
).properties(width=725, height=100)
track.view()
By replacing the Higlass server URL with a local path corresponding cistrome multivec file (4GB), gos automatically detects the local file and will starts a background Higlass server to power the visualization.
import gosling as gos
data = gos.multivec(
- url="https://server.gosling-lang.org/api/v1/tileset_info/?d=cistrome-multivec",
+ url='../data/cistrome.multires.mv5', # path to local multivec
row="sample",
column="position",
value="peak",
categories=["sample 1", "sample 2", "sample 3", "sample 4"],
binSize=4,
)
Important
Note that visualizations will only render as long as your Python session is active.