Journal: bioRxiv

Article Title: STCS: A Platform-Agnostic Framework for Cell-Level Reconstruction in Sequencing-Based Spatial Transcriptomics

doi: 10.64898/2026.02.26.708370

Figure Lengend Snippet: Performance of STCS on high-resolution Stereo-seq mouse brain data. A) Tissue images and segmentations. Left: original H&E image; Center: nuclei segmentation mask; Right: Single-cell Segmented slide by STCS (colored by cell class, defined as higher-level groupings of CellTypist-predicted cell types. B) Spatial continuity metrics. Left: Cell-class coherence across neighborhood size. computed as the proportion of spatially nearest neighbors sharing the same cell-class label at each neighborhood size. Higher values indicate greater spatial consistency of cell-class assignments within local tissue contexts. Middle: CHAOS scores computed at the Leiden cluster level. Right: CHAOS scores computed at the cell-class level. Lower CHAOS scores indicate better spatial organization. The center line represents the median CHAOS score and the box spans the interquartile range. The annotated text are µ ± σ . C) Gene Level metrics. Left: Cell-class label-transfer accuracy to a scRNA-seq reference across varying numbers of highly variable genes (HVGs), assessing how reliably reconstructed spatial cells recover reference-defined transcriptional identities and the robustness of predictions based on different selected features. Right: Distribution of gene-expression cosine similarity between reconstructed cells and scRNA-seq reference profiles across cell classes, quantifying transcriptomic agreement. Cosine similarity was computed between each reconstructed cell’s expression profile and the mean expression profile of its assigned cell class in the scRNA-seq reference. Center lines indicate medians and boxes span the interquartile range. The annotated text are µ ± σ . D) Cell-type composition accuracy. Left: Cell-type richness between methods and a single-cell reference data. Right: Absolute error in estimated cellclass proportions compared to the reference. Lower values indicate closer agreement with the cellular composition of the reference data. The annotated text are µ ± σ and center lines indicate median.

Article Snippet: The Stereo-seq whole mouse brain dataset is available from STOmics ( https://en.stomics.tech/col1241/index.html ).

Techniques: Single Cell, Gene Expression, Expressing

Journal: Molecular Therapy. Nucleic Acids

Article Title: TiSMeD: A tissue-specific methylation and expression database for biomarker and translational applications

doi: 10.1016/j.omtn.2026.102884

Figure Lengend Snippet: Overview of TiSMeD TiSMeD is a comprehensive resource that integrates 6,782 methylomes, 16,894 transcriptomes, and 241 proteomes obtained from multiple platforms. All datasets were processed using a standardized pipeline, resulting in the identification of 67,427 TSMs, 4,607 TSGs, and 2,833 TSPs based on tissue specificity and confidence score evaluation. In addition, TiSMeD includes 11,411,136 HKMs. TiSMeD features a user-friendly interface that enables data searching, browsing, downloading, and visualization.

Article Snippet: The transcriptome datasets were obtained from GEO, , the Genotype-Tissue Expression (GTEx) database, the Human Protein Atlas (HPA), and the RNA-seq Atlas.

Techniques: