Closed Marcel-Salier closed 2 years ago
This feature has already been implemented and added to the jupyter notebook (Cell #21). Fetch and pull the repository on Github Desktop to update to the latest version.
The code looks like this:
nga.plotDim(hue = "leiden", method="umap")
where hue
allows you to colour cells based on any variables (including leiden or louvain clusters).
Reopening this issue. I think I understood what you want. You want to be able to choose cells from a scatter plot and visualize the distribution of features (intensities or other nuclear features) for the chosen cells
I will add a function chooseCells
that allow lasso select data points from scatter plot and return a list of cells that can be used later.
Created chooseCells
function that will plot a scatter plot with axes of choice, and allow selection of points (cells) using lassoselector. Works in Jupyter Notebook and Python console by opening a new window to display plot. Function can be further refined, but it is ready for use.
d18fb410fadca518c21718f346595cac909359dd
We need visualization of the clusters after the UMAP. And probably people would like to extract a subgroup of cells based on a marker or feature and restart everything over again.