scLiTr is a Python package for analysis of lineage tracing coupled with single-cell RNA-Seq.
The main key of the package are clonal embeddings — vector representations of the whole clones in low dimensional space (clone2vec). These representations is a dropout-robust and cluster-free way of representation of heterogeneity within clonal behaviour for cell type tree-free hypothesis generation regarding cells' multipotency.
clone2vec builds representation of clones in exact same way with popular word embedding algorithm — word2vec — via construction two-layers fully connected neural network (specifically it uses Skip-Gram architecture) that aims to predict neighbour cells clonal labellings by clonal label of cells. As a result, clones that exist in similar context in gene expression space will have similar weights in this neural network, and these weights will be used as embedding for further analysis.
scLiTr might be installed via pip:
pip install sclitrPlease visit documentation web-site to check out API description and a few tutorials with analysis.
For interactive exploration of clonal and gene expression embeddings together we recommend using our simple tool clones2cells.
