Single-cell Software

Open-access analytical tools developed by our group:

1. SAVER: Single-cell Analysis Via Expression Recovery is an expression recovery method for scRNA-seq that borrows information across genes and cells to impute the zeros as well as to improve the expression estimates for all genes.

Open-source software for SAVER can be downloaded from:

2. SCALE: Single-cell RNA sequencing allows the comparison of expression distribution between the two alleles of a diploid organism and the characterization of allele-specific bursting. SCALE was developed to analyze genome-wide allele-specific bursting, with adjustment of technical variability. SCALE detects genes exhibiting allelic differences in bursting parameters and genes whose alleles burst non-independently.

SCALE is an open-source R package available at

3. TASC: Toolkit for Analysis of Single Cell RNA-seq is an empirical Bayes approach to reliably model the cell-specific dropout rates and amplification bias by use of external RNA spike-ins.

TASC is implemented in an open-source program (, with multithreading acceleration by openMP.

4. DESCEND: This method deconvolves the true cross-cell gene expression distribution from observed scRNA-seq counts, leading to improved estimates of properties of the distribution such as dispersion and burstiness.

The R package for DESCEND is available at:

5. MuSiC: MUlti-sample SIngle Cell deconvolution (MuSiC) utilizes cell-type specific gene expression from single-cell RNA sequencing (RNA-seq) data to characterize cell type compositions from bulk RNA-seq data in complex tissues. MuSiC enables characterization of cellular heterogeneity of complex tissues for identification of disease mechanisms.

The script to execute our deconvolution method can be obtained from: 

6. Semblance:  A rank-based Mercer kernel over probability spaces. Can be used to compute a pair-wise similarity metric, corresponding to informative representation of data. Available as an R package on CRAN.