Alignment and integration of spatial transcriptomics data | Nature Methods
PASTE aligns and integrates spatial transcriptomics data generated from adjacent tissue slices by leveraging their transcriptomic similarity and spatial coordinates, which ultimately increases the power for downstream analysis.
Subjects Data integration Genome informatics Abstract Spatial transcriptomics (ST) measures mRNA expression across thousands of spots from a tissue slice while recording the two-dimensional (2D) coordinates of each spot. We introduce probabilistic alignment of ST experiments (PASTE), a method to align and integrate ST data from multiple adjacent tissue slices. PASTE computes pairwise alignments of slices using an optimal transport formulation that models both transcriptional similarity and physical distances between spots. PASTE further combines pairwise alignments to construct a stacked 3D al
related reading
- Spatial Technology Offers Spectacular Insightsgenengnews.com
- Quantifying the effect of experimental perturbations at single-cell resolutionnature.com
- Museum of spatial transcriptomics | Nature Methodsnature.com
- The art of using t-SNE for single-cell transcriptomicsnature.com
- Peak calling with MACS2 | Introduction to ChIP-Seq using high-performance computinghbctraining.github.io
- Transcriptome assemblynbisweden.github.io
- How I Understand Flow Matchingyoutube.com
- A survey of best practices for RNA-seq data analysisgenomebiology.biomedcentral.com
- The Dawn of Spatial Medicinesubstack.com
- Universal consensus 3D segmentation of cells from 2D segmented stacks | Nature Methodsnature.com
- Sliced Score Matching: A Scalable Approach to Density and Score Estimation | Yang Songyang-song.github.io
- Point-set registrationen.wikipedia.org