Please check our Github page for a complete list of computational tools developed in the lab. We highlight a few below (some of them are not in Github).
Paper websites
SPRING
SPRING is a tool for uncovering high-dimensional structure in single-cell gene expression data. SPRING takes a (gene X cell) table of expression measurements and outputs a k-nearest-neighbor graph rendered using a force directed layout. Users can overlay prior information, including gene expression values, gene-set scores, cell cluster labels and sample IDs. Users can also upload custom coordinates that have been generated using an outside program such as UMAP. See here.
Indrops
A detailed protocol for indrops single cell RNA-Seq can be found here.
A pre-processing pipeline parsing raw sequencing data into a cell-by-gene count matrix can be found here.
CoSpar
CoSpar is a toolkit for dynamic inference from lineage-traced single cells. The methods are based on Wang et al. Nat. Biotech. (2022). See the documentation website and an accompanying talk video https://youtu.be/HrDQpW3kJFo.
Single-Cell Remover of Doublets
Python code for identifying doublets in single-cell RNA-seq data can be found here.
Scrublet
Population balance analysis
Population balance analysis (PBA) relates the observed states of a system to its steady-state dynamics by applying the law of population balance. A landscape is inferred based on a snapshot of the single-cell transcriptome of the tissue, which allows to predict the fate bias of a given state and potentially its trajectory. The python code can be found here.
LARRY
Pipelines for high-throughput lentiviral lineage tracing simultaneously with scRNA-Seq can be found here.