Search engine for discovering works of Art, research articles, and books related to Art and Culture
Javascript must be enabled to continue!
SpaBatch: Batch Alignment of Spatial Transcriptomics Data using Graph Deep Learning
View through CrossRef
AbstractSpatial transcriptomics (ST) has emerged as a transformative technology, enabling the simultaneous capture of gene expression and spatial context within tissues. However, batch effects arising from technical variability remain a significant barrier to integrating datasets generated from different experiments. To this end, we introduce a novel graph deep learning framework (SpaBatch) tailored for the batch alignment of multi-slice spatial transcriptomics data. SpaBatch is an innovative computational framework leveraging Variational Graph Autoencoders, self-supervised learning, and triplet learning with readout aggregation to enhance multi-slice spatial transcriptomics data integration. We validated our framework on multiple datasets encompassing various tissue types and experimental conditions. Through the adjustment of batch effects, SpaBatch facilitates the analysis of spatial transcriptome domains across multiple slices, showcasing its capability to reveal new biological insights in multi-slice spatial transcriptome studies.
Title: SpaBatch: Batch Alignment of Spatial Transcriptomics Data using Graph Deep Learning
Description:
AbstractSpatial transcriptomics (ST) has emerged as a transformative technology, enabling the simultaneous capture of gene expression and spatial context within tissues.
However, batch effects arising from technical variability remain a significant barrier to integrating datasets generated from different experiments.
To this end, we introduce a novel graph deep learning framework (SpaBatch) tailored for the batch alignment of multi-slice spatial transcriptomics data.
SpaBatch is an innovative computational framework leveraging Variational Graph Autoencoders, self-supervised learning, and triplet learning with readout aggregation to enhance multi-slice spatial transcriptomics data integration.
We validated our framework on multiple datasets encompassing various tissue types and experimental conditions.
Through the adjustment of batch effects, SpaBatch facilitates the analysis of spatial transcriptome domains across multiple slices, showcasing its capability to reveal new biological insights in multi-slice spatial transcriptome studies.
Related Results
SpaBatch: Deep Learning‐Based Cross‐Slice Integration and 3D Spatial Domain Identification in Spatial Transcriptomics
SpaBatch: Deep Learning‐Based Cross‐Slice Integration and 3D Spatial Domain Identification in Spatial Transcriptomics
AbstractWith the rapid accumulation of spatial transcriptomics (ST) data across diverse tissues, individuals, and technological platforms, there is an urgent need for a robust and ...
Performance of Multiple-Batch Approaches to Pharmacokinetic Bioequivalence Testing for Orally Inhaled Drug Products with Batch-to-Batch Variability
Performance of Multiple-Batch Approaches to Pharmacokinetic Bioequivalence Testing for Orally Inhaled Drug Products with Batch-to-Batch Variability
AbstractBatch-to-batch pharmacokinetic (PK) variability of orally inhaled drug products has been documented and can render single-batch PK bioequivalence (BE) studies unreliable; r...
Imputation of Spatially-resolved Transcriptomes by Graph-regularized Tensor Completion
Imputation of Spatially-resolved Transcriptomes by Graph-regularized Tensor Completion
Abstract
High-throughput spatial-transcriptomics RNA sequencing (sptRNA-seq) based on in-situ capturing technologies has recently been developed ...
Graph convolutional neural networks for 3D data analysis
Graph convolutional neural networks for 3D data analysis
(English) Deep Learning allows the extraction of complex features directly from raw input data, eliminating the need for hand-crafted features from the classical Machine Learning p...
Contribuición al estudio de la operación de destilación discontinua mediante simulación
Contribuición al estudio de la operación de destilación discontinua mediante simulación
El treball presentat en aquesta tesi pretén contribuir a l'estudi mediambiental de la limitació de les emissions de components orgànics volàtils (VOCs), degudes a l'ús de dissolven...
Graph data warehousing
Graph data warehousing
Over the last decade, we have witnessed the emergence of networks in a wide spectrum of application domains, ranging from social and information networks to biological and transpor...
The impact of environmental uncertainty on business–IT alignment: A study in Sri Lanka
The impact of environmental uncertainty on business–IT alignment: A study in Sri Lanka
<p>Despite the widely held belief that organisational performance can be enhanced through the alignment of information technology (IT) and business strategy, alignment remain...
CREATING LEARNING MEDIA IN TEACHING ENGLISH AT SMP MUHAMMADIYAH 2 PAGELARAN ACADEMIC YEAR 2020/2021
CREATING LEARNING MEDIA IN TEACHING ENGLISH AT SMP MUHAMMADIYAH 2 PAGELARAN ACADEMIC YEAR 2020/2021
The pandemic Covid-19 currently demands teachers to be able to use technology in teaching and learning process. But in reality there are still many teachers who have not been able ...