Downloaded over 20,000 times and cited in over 400 peer-reviewed publications. AltAnalyze has hundreds of active users and is being actively developed as an open-source project.

AltAnalyze recieves funding from NIH National Cancer Institute (R01CA226802).


: See our new manuscripts describing the AltAnalyze workflows ICGS2 and cellHarmony and their application, in new article in Nature.




Iterative Clustering and Guide gene Selection (ICGS)
Unsupervised Single-Cell Expression Profile Identification

A significant challenge in the analysis of single-cell RNA-Seq gene expression profiles is the unbiased identification of the most coherent, correlated gene signatures that are able to segregate distinct developmental states or cell-types without prior knowledge. As a means to do this, we development an algorithm (ICGS) in AltAnalyze, that ultimately identifies those genes and transcription factors that correspond to the predominant expression signatures present in a sample, while excluding signatures that are likely stochastic or isolated to a single sample. ICGS can be run prior to performing group comparison analyses or on it's own.