clones2cells

Simple Streamlit application for interactive exploratory analysis of clonal embeddings. For more info on how to construct clonal embeddings please see scLiTr package.

Web-page with application

Please visit https://clones2cells.streamlit.app to explore datasets from the paper Erickson, Isaev et al.

How to use it locally

To run clones2cells locally, firstly, install dependencies:

pip install streamlit plotly streamlit_plotly_events pandas

After that, run the following command from the terminal:

streamlit run https://raw.githubusercontent.com/serjisa/clones2cells_app/main/clones2cells_viewer.py --theme.base light

Streamlit clones2cells app should be opened after execution of this command — and here you will be able to select files that you got from prepare_clones2cells function of scLiTr package (one csv-file for clonal embedding and one csv-file for gene expression embedding).

You also may use tables generated by your own: in this case make sure that (a) the first column of each table is an index, (b) index from clonal csv-file corresponds to the clonal labelling from the column clone in gene expression csv-file, (c) both tables have columns UMAP1 and UMAP2.

Example: clonal embedding and gene expression embedding.