Discovering Condition-specific Cell Populations via Integrative Clustering of Single-cell Data

Abstract

We present INtegrative CLustering Of Single cElls (INCLOSE), a novel computational method that integrates single-cell omics data and sample metadata to identify cell populations. INCLOSE analysis of CITE-seq data of acute myeloid leukemia and healthy samples uncovered cell populations exclusively found in the leukemia samples or the healthy samples. These condition-specific cell populations strongly suggested that immune suppression in tumor microenvironment plays a pivotal role in driving tumor progression.