Selected Publications

The rapid development of novel spatial transcriptomics technologies has provided new opportunities to investigate the interactions between cells and their native microenvironment. However, effective use of such technologies requires the development of innovative computational algorithms and pipelines. Here we present Giotto, a comprehensive, flexible, robust, and open-source pipeline for spatial transcriptomic data analysis and visualization. The data analysis module implements a wide range of algorithms ranging from basic tasks such as data pre-processing to innovative approaches for cell-cell interaction characterization. The data visualization module provides a user-friendly workspace that allows users to interactively visualize, explore and compare multiple layers of information. These two modules can be used iteratively for refined analysis and hypothesis development. We illustrate the functionalities of Giotto by using the recently published seqFISH+ dataset for mouse brain. Our analysis highlights the utility of Giotto for characterizing tissue spatial organization as well as for the interactive exploration of multi- layer information in spatial transcriptomic and imaging data. We find that single-cell resolution spatial information is essential for the investigation of ligand-receptor mediated cell-cell interactions. Giotto is generally applicable and can be easily integrated with external software packages for multi-omic data integration.
In BioRxiv.,2019

Recent Publications

More Publications

. CDK7 Inhibition Potentiates Genome Instability Triggering Anti-tumor Immunity in Small Cell Lung Cancer.. In Cancer Cell., 2020.

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. Integrative and perturbation based analysis of the transcriptional dynamics of TGFβ/BMP system components in transition from embryonic stem cells to neural progenitors.. In Stem Cells., 2019.

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. BORIS promotes chromatin regulatory interactions in treatment-resistant cancer cells.. In Nature., 2019.

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. Giotto, a pipeline for integrative analysis and visualization of single-cell spatial transcriptomic data.. In BioRxiv., 2019.

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. RESCUE: imputing dropout events in single- cell RNA-sequencing data.. In BMC Bioinformatics., 2019.

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. CDK12 loss in cancer cells affects DNA damage response genes through premature cleavage and polyadenylation.. In Nature Communications., 2019.

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. Transcriptome-scale super-resolved imaging in tissues by RNA seqFISH+. In Nature., 2019.

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. NK cells mediate synergistic antitumor effects of combined inhibition of HDAC6 and BET in a SCLC preclinical model.. In Cancer Research., 2018.

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. Genomic and functional fidelity of small cell lung cancer patient-derived xenografts.. In Cancer Discovery., 2018.

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Spatial Expression

Exploration of the spatial cellular microenvironment. What are the sources of spatial variability? How do cells communicate? How can we integrate different spatial and single-cell technologies?


Cancer genomics


Immunology in cancer


Exploration of single-cell genomics

Stem Cells

Stem cells and embryonic development


Transcriptional regulation