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Feb 27, 2024 · We have described BANKSY, a spatial clustering algorithm that unifies cell typing and tissue domain segmentation under a single, scalable machine-learning framework with minimal free parameters...

BANKSY is a method for clustering spatial omics data by augmenting the features of each cell with both an average of the features of its spatial neighbors along with neighborhood feature gradients. By incorporating neighborhood information for clustering, BANKSY is able to.

BANKSY is a method for clustering spatial omics data by augmenting the features of each cell with both an average of the features of its spatial neighbors along with neighborhood feature gradients. By incorporating neighborhood information for clustering, BANKSY is able to.

May 15, 2024 · BANKSY encodes the microenvironment of a cell using a pair of spatial kernels: one constructed using the weighted mean of gene expression in each cell’s neighbourhood, and the other using an...

Apr 15, 2022 · We present BANKSY, an algorithm that unifies cell type clustering and domain segmentation by constructing a product space of cell and neighbourhood transcriptomes, representing cell state and microenvironment, respectively.

BANKSY revealed unexpected niche-dependent cell states in the mouse brain and outperformed competing methods on domain segmentation and cell typing benchmarks. BANKSY can also be used for quality control of spatial transcriptomics data …

BANKSY is an algorithm with R and Python implementations that identifies both cell types and tissue domains from spatially resolved omics data by incorporating spatial kernels capturing microenvironmental information. It is applicable to a range of technologies and is scalable to millions of cells.

Apr 15, 2022 · BANKSY’s spatial kernel-based feature augmentation strategy improves per-formance and scalability on both tasks when tested on FISH-based and sequencing-based spatial omics data. Uniquely,...

To incorporate spatial information, BANKSY computes the mean neighborhood expression and azimuthal Gabor filters that capture gene expression gradients.

Apr 15, 2022 · BANKSY’s spatial kernel-based feature augmentation strategy improves per-formance and scalability on both tasks when tested on FISH-based and sequencing-based spatial omics data. Uniquely, BANKSY identified hitherto undetected niche-dependent cell states in two mouse brain regions.

large datasets. BANKSY is 1–3 orders of magnitude faster than existing spatial methods and scales to >2 million cells with similar run times as state-of-the-art non-spatial clustering methods.

Jul 5, 2022 · We present BANKSY, an algorithm that unifies cell type clustering and domain segmentation by constructing a product space of cell and neighborhood transcriptomes, representing cell state and microenvironment, respectively.

BANKSY revealed unexpected niche-dependent cell states in the mouse brain and outperformed competing methods on domain segmentation and cell typing benchmarks. BANKSY can also be used for quality control of spatial transcriptomics data …

Dec 20, 2024 · The BANKSY algorithm employs a neighbourhood kernel with a feature augmentation approach to analyse data from various spatial omics technologies, such as RNA sequencing and protein imaging, significantly improving cell classification and tissue analysis.

Feb 27, 2024 · BANKSY revealed unexpected niche-dependent cell states in the mouse brain and outperformed competing methods on domain segmentation and cell typing benchmarks. BANKSY can also be used for quality control of spatial transcriptomics data and for spatially aware batch effect correction.

Feb 27, 2024 · In this issue, Singhal et al. 4 present BANKSY, a new spatial clustering algorithm that implements a creative feature-augmentation approach to better map domains by integrating the...

2 Spatial and Single Cell Systems Domain, Genome Institute of Singapore, Singapore, Republic of Singapore. PMID: 38750154 DOI: 10.1038/s41576-024-00743-9

BANKSY revealed unexpected niche-dependent cell states in the mouse brain and outperformed competing methods on domain segmentation and cell typing benchmarks. BANKSY can also be used for quality control of spatial transcriptomics data …

Apr 14, 2022 · BANKSY is a spatial omics clustering algorithm that unifies spatial cell type clustering and domain segmentation into a single scalable framework. It does this by utilizing the spatial microenvironment to augment the transcriptomes of cells, allowing for the discovery of niche-dependent cell subtypes, more accurate clustering, and the ...

Apr 14, 2022 · The study proposes a new method called BANKSY for clustering spatial omics profiles. Given a cell by omic feature values matrix, the idea is to concatenate, for each cell, the vector of its features with a vector of the average omic features of its neighbourhood.