Cell type identification in spatial transcriptomics data can be improved by leveraging cell-type-informative paired tissue images using a Bayesian probabilistic model

Cell2location maps fine-grained cell types in spatial transcriptomics

(2022) Vitalii Kleshchevnikov et al.   NATURE BIOTECHNOLOGY

SPOTlight: seeded NMF regression to deconvolute spatial transcriptomics spots with single-cell transcriptomes

(2021) Marc Elosua-Bayes et al.   NUCLEIC ACIDS RESEARCH

Neuroblastoma formation requires unconventional CD4 T cells and Arginase-1-dependent myeloid cells.

(2021) Lee-Ann Van de Velde et al.   CANCER RESEARCH

Separating measurement and expression models clarifies confusion in single-cell RNA sequencing analysis

(2021) Abhishek Sarkar et al.   NATURE GENETICS

Integrating microarray-based spatial transcriptomics and single-cell RNA-seq reveals tissue architecture in pancreatic ductal adenocarcinomas

(2020) Reuben Moncada et al.   NATURE BIOTECHNOLOGY

Statistical analysis of spatial expression patterns for spatially resolved transcriptomic studies

(2020) Shiquan Sun et al.   NATURE METHODS

Single-cell and spatial transcriptomics enables probabilistic inference of cell type topography

(2020) Alma Andersson et al.   Communications Biology

High-Spatial-Resolution Multi-Omics Sequencing via Deterministic Barcoding in Tissue

(2020) Yang Liu et al.   CELL

Highly sensitive spatial transcriptomics at near-cellular resolution with Slide-seqV2

(2020) Robert R. Stickels et al.   NATURE BIOTECHNOLOGY

Slide-seq: A scalable technology for measuring genome-wide expression at high spatial resolution

(2019) Samuel G. Rodriques et al.   SCIENCE

Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology

(2019) Gregor Sturm et al.   BIOINFORMATICS

Probabilistic cell-type assignment of single-cell RNA-seq for tumor microenvironment profiling

(2019) Allen W. Zhang et al.   NATURE METHODS

High-definition spatial transcriptomics for in situ tissue profiling

(2019) Sanja Vickovic et al.   NATURE METHODS

Modeling Cell-Cell Interactions from Spatial Molecular Data with Spatial Variance Component Analysis

(2019) Damien Arnol et al.   Cell Reports

SpatialDE: identification of spatially variable genes

(2018) Valentine Svensson et al.   NATURE METHODS

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

(2018) Joel Saltz et al.   Cell Reports

Unravelling subclonal heterogeneity and aggressive disease states in TNBC through single-cell RNA-seq

(2018) Mihriban Karaayvaz et al.   Nature Communications

Estimation of immune cell content in tumour tissue using single-cell RNA-seq data

(2017) Max Schelker et al.   Nature Communications

Robust enumeration of cell subsets from tissue expression profiles

(2015) Aaron M Newman et al.   NATURE METHODS

Association of PD-1, PD-1 Ligands, and Other Features of the Tumor Immune Microenvironment with Response to Anti-PD-1 Therapy

(2014) J. M. Taube et al.   CLINICAL CANCER RESEARCH

DeconRNASeq: a statistical framework for deconvolution of heterogeneous tissue samples based on mRNA-Seq data

(2013) Ting Gong et al.   BIOINFORMATICS

Tumor-infiltrating immune cells and prognosis: the potential link between conventional cancer therapy and immunity

(2011) Caroline Jochems et al.   EXPERIMENTAL BIOLOGY AND MEDICINE

Model-Based Clustering of Non-Gaussian Panel Data Based on Skew-tDistributions

(2009) Miguel A. Juárez et al.   JOURNAL OF BUSINESS & ECONOMIC STATISTICS