nnSVG for the scalable identification of spatially variable genes using nearest-neighbor Gaussian processes
Feature selection to identify spatially variable genes or other biologically informative genes
is a key step during analyses of spatially-resolved transcriptomics data. Here, we propose …
is a key step during analyses of spatially-resolved transcriptomics data. Here, we propose …
MAPLE: a hybrid framework for multi-sample spatial transcriptomics data
Motivation The advent of high throughput spatial transcriptomics (HST) technologies has
allowed for characterization of spatially and genetically distinct cell sub-populations in tissue …
allowed for characterization of spatially and genetically distinct cell sub-populations in tissue …
A bayesian multivariate mixture model for spatial transcriptomics data
High throughput spatial transcriptomics (HST) is a rapidly emerging class of experimental
technologies that allow for profiling gene expression in tissue samples at or near single-cell …
technologies that allow for profiling gene expression in tissue samples at or near single-cell …
Bayesian Models for High Throughput Spatial Transcriptomics
C Allen - 2022 - rave.ohiolink.edu
High throughput spatial transcriptomics (HST) is a rapidly emerging class of experimental
technologies that allow for profiling gene expression in tissue samples at or near single-cell …
technologies that allow for profiling gene expression in tissue samples at or near single-cell …