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

Mudappathi, R.; Vaishali, B.; Liu, L.

doi:10.1101/2025.10.03.680413

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bioRxiv · 10.1101/2025.10.03.680413

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

Mudappathi, R.·Vaishali, B.·Liu, L.

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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.

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Mudappathi, R., Vaishali, B., Liu, L.. 2025-10-06. Discovering Condition-specific Cell Populations via Integrative Clustering of Single-cell Data. https://doi.org/10.1101/2025.10.03.680413

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