Epidemiology & Biostatistics

The Ruslan Soldatov Lab


Ruslan Soldatov
Ruslan Soldatov, PhD
Assistant Attending

Assistant Professor

The Soldatov Lab aims to characterize the mechanisms of cell fate decisions that coordinate tissue function and quantify how distortions of these mechanisms shape the course of cancer evolution. We are broadly interested in using a large-scale data science approach to study questions related to the organization of normal tissues and cancer, viewing it as a dynamic ecosystem of fundamental units — cells. We study the impact of stem cell heterogeneity on tissue function. In particular, we focus on the role of stem cell phenotypes, such as proliferative capacity or regenerative potential, in cancer initiation and evolution. We seek to characterize how regulatory circuits enable phenotypic plasticity to emerge, allowing cancers to evolve and evade treatments. Finally, we are interested in how the microenvironment and external insults, such as injury or pathogens, reshape cell fate decisions. To advance these questions, we develop computational methods to analyze cellular heterogeneity using high-throughput measurements at the level of individual cells. The lab leverages machine learning approaches, dynamic systems theory, and data science to gain insights into the evolution of tissue ecosystems in the context of basic and translational science.

The Soldatov Lab

Publications Highlights

Faure L, Soldatov R, Kharchenko PV, Adameyko I. scFates: a scalable python package for advanced pseudotime and bifurcation analysis from single-cell data. Bioinformatics. 2023 Jan 1;39(1):btac746. doi: 10.1093/bioinformatics/btac746. PMID: 36394263; PMCID: PMC9805561.

Gao T, Soldatov R, Sarkar H, Kurkiewicz A, Biederstedt E, Loh PR, Kharchenko PV. Haplotype-aware analysis of somatic copy number variations from single-cell transcriptomes. Nat Biotechnol. 2022 Sep 26. doi: 10.1038/s41587-022-01468-y. Epub ahead of print. PMID: 36163550

Petukhov V, Xu RJ, Soldatov RA, Cadinu P, Khodosevich K, Moffitt JR, Kharchenko PV. Cell segmentation in imaging-based spatial transcriptomics. Nat Biotechnol. 2022 Mar;40(3):345-354. doi: 10.1038/s41587-021-01044-w. Epub 2021 Oct 14. PMID: 34650268

Bergen V, Soldatov RA, Kharchenko PV, Theis FJ. RNA velocity-current challenges and future perspectives. Mol Syst Biol. 2021 Aug;17(8):e10282. doi: 10.15252/msb.202110282. PMCID: PMC8388041. PMID: 34435732

Seplyarskiy VB, Soldatov* RA, et al; NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium; TOPMed Population Genetics Working Group, Gilissen C, Wong WSW, Kharchenko PV, Sunyaev S. Population sequencing data reveal a compendium of mutational processes in the human germ line. Science. 2021 Aug 27;373(6558):1030-1035. doi: 10.1126/science.aba7408. Epub 2021 Aug 12. PMCID: PMC9217108. PMID: 34385354

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Ruslan Soldatov

Ruslan Soldatov, PhD

Assistant Attending

Assistant Professor

  • Computational biologist Ruslan Soldatov develops computational methods to study cell fate decisions and somatic evolution in normal tissues and cancer.
[email protected]
Email Address


Louis Faure

Postdoctoral Fellow

Luan Le

Postdoctoral Fellow

Aleksei Pakharev

Postdoctoral Fellow

Chi-Lam Poon

PhD Student

Lab Affiliations

Open Positions

To learn more about available postdoctoral opportunities, please visit our Career Center

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Postdoctoral Fellow in computational single-cell genomics

Successful candidates will drive key research questions that cross cut the themes of somatic evolution, regulation of cell fate decisions, and organization of the microenvironment. The projects will involve analysis of multi-omics, pooled perturbations and spatially-resolved datasets.

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Doctors and faculty members often work with pharmaceutical, device, biotechnology, and life sciences companies, and other organizations outside of MSK, to find safe and effective cancer treatments, to improve patient care, and to educate the health care community.

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Ruslan Soldatov discloses the following relationships and financial interests:

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