MCBrowse 0.1.0-dev.1 - Metacells Browsing¶

Context¶

The mcbrowse package provides utilities for browsing the content of metacells data stored in a daf repository, typically created by using the metacells package.

These utilities are meant to be used in two main ways:

Directly using plotly, either inside jupyter notebooks, inside dash applications, or in standalone HTML files; or
From inside an R environment, using reticulate and (TODO) the matching mcbrowser packages (note the r at the end).

The utilities provided here allow generating figures in distinct steps: (1) extracting the tidy data data needed for a specific figure from the overall metacells daf repository, (2) specifying parameters to control the figure appearance in a veneer object and (3) generating a plotly figure. The matching R package provides utilities that take the same data and veneer objects (accessed via reticulate) and produce a ggplot figure.

One can use this in a pure script form, manually specifying all the parameters, or one can use the provided jupyter notebook ipywidgets to use a friendly UI to control the parameters.

See the documentation for the full API details.

Usage¶

Simple usage in Python:

import daf
import mcbrowse

# Open some metacells data repository.
data = daf.DafReader(...)

# Extract the data for a gene-gene figure.
figure_data = mcbrowse.GeneGeneData(...)

# Control what the figure will look like.
figure_veneer = mcbrowse.GeneGeneVeneer(...)

# Obtain a plotly figure.
figure = GeneGeneFigure(figure_data, figure_veneer)

figure.show()

And equivalent usage in R:

require(reticulate)
require(mcbrowser)
require(ggplot2)

daf <- reticulate::import("daf")
mcbrowse <- reticulate$import("mcbrowse")

# Open some metacells data repository.
data <- daf$DafReader(...)

# Extract the data for a gene-gene figure.
figure_data <- mcbrowse$GeneGeneFilter(...).collect()

# Control what the figure will look like.
figure_veneer <- mcbrowse$GeneGeneVeneer(...)

# Obtain a ggplot figure.
figure = figure_veneer.plot(figure_data)

print(figure)

Installation¶

In short: pip install mcbrowse. Note that mcbrowse requires many “heavy” dependencies, most notably daf which in turn requires numpy, pandas, scipy and anndata, all of which pip should automatically install for you. If you are running inside a conda environment, you might prefer to use it to first install these dependencies, instead of having pip install them from PyPI.

License (MIT)¶

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.