| 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. |
