Journal: bioRxiv

Article Title: Single-cell transcriptomic atlas of mouse oocyte development from growth to ovulation

doi: 10.64898/2026.03.11.710939

Figure Lengend Snippet: a , UMAP of GCs, colored by seven GC subtypes (Progenitor, Preantral 1, Preantral 2, Mitotic 1, Mitotic 2, Antral Mural and Atretic). b , Feature plots of representative subtype markers on the UMAP. c , Monocle3 pseudotime trajectory inferred for GCs, with the principal graph overlaid and direction indicated from progenitor toward antral mural cells. d , Heatmap of representative genes showing coordinated expression changes along the progenitor-to-mural trajectory (expression shown as z-scores). e , Heatmap of Hallmark ssGSEA scores across granulosa subtypes (z-scored per gene set). f , H&E image of a Stereo-seq FF V1.3 mouse ovary section (6-8 weeks old), with representative regions (α–θ) indicated. Scale bar, 100 μm. g , Cell2location-based spatial mapping of GC subtypes at cell-bin resolution. h , Zoom-in views of representative regions (α, β, γ, and θ) showing H&E morphology and spatial expression of selected marker genes. Scale bar, 50 μm.

Article Snippet: Publicly available mouse ovary Stereo-seq Transcriptomics FF v1.3 demo data were obtained from the STOmics website ( https://www.stomics.tech/col1347 ).

Techniques: Expressing, Marker

Journal: bioRxiv

Article Title: Single-cell transcriptomic atlas of mouse oocyte development from growth to ovulation

doi: 10.64898/2026.03.11.710939

Figure Lengend Snippet: Spatial maps showing cell2location-predicted localization of each annotated cell subtype on the Stereo-seq FF V1.3 ovary section (6–8 weeks old), displayed separately by subtype. Scale bar, 100 μm

Article Snippet: Publicly available mouse ovary Stereo-seq Transcriptomics FF v1.3 demo data were obtained from the STOmics website ( https://www.stomics.tech/col1347 ).

Techniques:

Journal: Frontiers in Immunology

Article Title: Decoding the spatial logic of immune evasion in hepatocellular carcinoma: from single-cell profiling to spatial omics

doi: 10.3389/fimmu.2026.1935648

Figure Lengend Snippet: Comprehensive comparison of scRNA-seq and spatial omics technologies in oncology.

Article Snippet: Sequencing-based spatial transcriptomics , Visium (10x Genomics); Stereo-seq (BGI); Slide-seq , Whole-transcriptome mapping across large tissue areas; resolution ranges from multi-cellular spots to subcellular/nanoscale platforms. , Maps tissue-scale architecture, spatial gene modules, subclonal competition zones and tumor-stroma boundaries. , Resolution-sensitivity trade-off; multi-cellular spots require deconvolution; high sequencing cost..

Techniques: Comparison, Single Cell, Profiling, Sample Throughput, Sequencing, Spatial Transcriptomics, Tissue, Imaging, Sampling, In Situ, Transcriptomics, Functional Assay, Multiplexing, Biomarker Discovery

Journal: Nature Methods

Article Title: Inferring allele-specific copy number aberrations and tumor phylogeography from spatially resolved transcriptomics

doi: 10.1038/s41592-024-02438-9

Figure Lengend Snippet: a , Inputs to CalicoST are transcript counts X 0 , allele counts Y 0 and D 0 , spatial coordinates S from one or more SRT slices or a 3D alignment of slices. b , CalicoST phases input alleles in Y 0 and D 0 using a database of haplotypes. Optionally, CalicoST infers tumor proportion per spot using the BAF. CalicoST jointly models transcript counts and allele counts as functions of allele-specific copy number states within each clone. CalicoST uses an HMM to model correlations between copy number states from adjacent genomic regions and a HMRF to model correlations between the cancer clones assigned to neighboring spatial locations. c , CalicoST infers allele-specific integer copy numbers for one or more cancer clones, a phylogeny relating these clones, a clone label, an optional tumor proportion for each spot and a phylogeographic model of the spatial expansion of cancer clones.

Article Snippet: We applied CalicoST to infer allele-specific copy numbers on 10x Genomics Visium Spatial Transcriptomics data from 12 patients (26 slices) in HTAN (WashU cohort) across three cancer types (‘Running CalicoST on SRT data’).

Techniques: Clone Assay

Journal: Nature Methods

Article Title: Inferring allele-specific copy number aberrations and tumor phylogeography from spatially resolved transcriptomics

doi: 10.1038/s41592-024-02438-9

Figure Lengend Snippet: a , Accuracy of allele-specific copy numbers across 12 patients from HTAN (WashU cohort) inferred by CalicoST. Each bar represents an inferred cancer clone. b , Length distribution of CNAs identified by CalicoST from SRT data and identified by HATCHet2 from WES for the 9 patients with matched WES data of sufficient tumor purity. Blue bars are CalicoST, and orange bars are HATCHet2, with gray bars indicating the overlap of the two histograms. The median length is 77.4 Mb for CalicoST and 30 Mb for HATCHet2 (vertical dashed lines). c , Allele-specific integer copy numbers inferred by CalicoST from SRT data from a patient with CRC liver metastasis (HT230C1). Rows are cancer clones, and columns are genomic bins. Colors indicate allele-specific copy numbers. d , Allele-specific integer copy numbers inferred by CalicoST from SRT data from a patient with CRC liver metastasis (HT260C1). e , Observed RDR and BAF for chr8 of HT260C1. Points are colored by the inferred allele-specific copy numbers. Horizontal black lines indicate the RDR and BAF of the corresponding copy number states estimated by the HMM. f , Allele-specific integer copy numbers inferred by HATCHet2 from WES data of patient HT260C1. g , RDR and BAF values from WES data for bins from chromosome 8q and bins from other genomic regions with a value of {3,0} copy number state. Black points are expected RDR and BAF values for {3,0} and {2,1} states from HATCHet2 analysis.

Article Snippet: We applied CalicoST to infer allele-specific copy numbers on 10x Genomics Visium Spatial Transcriptomics data from 12 patients (26 slices) in HTAN (WashU cohort) across three cancer types (‘Running CalicoST on SRT data’).

Techniques: Clone Assay

Journal: Nature Methods

Article Title: Inferring allele-specific copy number aberrations and tumor phylogeography from spatially resolved transcriptomics

doi: 10.1038/s41592-024-02438-9

Figure Lengend Snippet: ( a ) CalicoST-inferred cancer clones in PDAC patient HT270P1. Grayscale indicates the inferred tumor proportion within each spot, where more gray indicates a higher proportion of normal cells (lower tumor proportion). ( b ) RDR and BAF along the genome for each inferred clone in HT270P1. Each point represents a genomic bin and is colored by CalicoST-inferred allele-specific copy numbers. The red box highlights a unique deletion in clone 2. ( c – d ) Corresponding plots for PDAC patient HT288P1. Red boxes highlight deletions that are unique to one of the inferred clones.

Article Snippet: We applied CalicoST to infer allele-specific copy numbers on 10x Genomics Visium Spatial Transcriptomics data from 12 patients (26 slices) in HTAN (WashU cohort) across three cancer types (‘Running CalicoST on SRT data’).

Techniques: Clone Assay

Journal: Nature Methods

Article Title: Inferring allele-specific copy number aberrations and tumor phylogeography from spatially resolved transcriptomics

doi: 10.1038/s41592-024-02438-9

Figure Lengend Snippet: H&E images (top) and CalicoST-inferred tumor proportions (bottom) for breast cancer samples: ( a ) HT206B1, ( b ) HT339B1, ( c ) HT268B1, ( d ) HT265B1. The x- and y-axes represent spatial coordinates. The color bar indicates the inferred tumor proportions.

Article Snippet: We applied CalicoST to infer allele-specific copy numbers on 10x Genomics Visium Spatial Transcriptomics data from 12 patients (26 slices) in HTAN (WashU cohort) across three cancer types (‘Running CalicoST on SRT data’).

Techniques:

Journal: Nature Methods

Article Title: Inferring allele-specific copy number aberrations and tumor phylogeography from spatially resolved transcriptomics

doi: 10.1038/s41592-024-02438-9

Figure Lengend Snippet: The plots for CalicoST include the allele-specific CNAs from all inferred cancer clones, labeled as ‘clone 1’, ‘clone 2’, etc. The plots for HATCHet2, labeled as ‘WES’, are included for the nine patients for whom matched WES data is available and has sufficient tumor purity.

Article Snippet: We applied CalicoST to infer allele-specific copy numbers on 10x Genomics Visium Spatial Transcriptomics data from 12 patients (26 slices) in HTAN (WashU cohort) across three cancer types (‘Running CalicoST on SRT data’).

Techniques: Clone Assay, Labeling

Journal: Nature Methods

Article Title: Inferring allele-specific copy number aberrations and tumor phylogeography from spatially resolved transcriptomics

doi: 10.1038/s41592-024-02438-9

Figure Lengend Snippet: a , b , Accuracy ( a ) and spatial coherence ( b ) comparison among CalicoST, Numbat, InferCNV and STARCH on CRC liver metastasis patient samples. Solid bars indicate predictions of allele-specific copy number states, and dotted bars indicate predictions of total copy number states. c , H&E image of a CRC liver metastasis sample HT260C1. d , Cancer clones inferred by CalicoST. x and y axes are spatial coordinates, and the grayscale represents the proportion of normal cells within each spot, as inferred by RCTD. Other colors indicate cancer clones. e , Cancer clones inferred by Numbat using the same color scheme as in d .

Article Snippet: We applied CalicoST to infer allele-specific copy numbers on 10x Genomics Visium Spatial Transcriptomics data from 12 patients (26 slices) in HTAN (WashU cohort) across three cancer types (‘Running CalicoST on SRT data’).

Techniques: Comparison, Starch, Clone Assay

Journal: Nature Methods

Article Title: Inferring allele-specific copy number aberrations and tumor phylogeography from spatially resolved transcriptomics

doi: 10.1038/s41592-024-02438-9

Figure Lengend Snippet: ( a ) Accuracy of the allele-specific copy number states inferred by CalicoST and Numbat on nine HTAN patients where ‘ground truth’ CNAs were inferred from matched WES data. ( b ) Spatial coherence of the cancer clones inferred by CalicoST and Numbat. The spatial coherence is evaluated by the z-score of joincount statistics, with higher values indicating a greater degree of spatial coherence. Each point represents a cancer clone within each slice of each patient (x-axis). As the two methods identify different numbers of clones, the two boxes include varying numbers of points for each patient. From left to right, the numbers of points in the boxplots are: HT112C1 (6 for CalicoST and 11 for Numbat), HT260C1 (3 for CalicoST and 6 for Numbat), HT265B1 (3 for CalicoST and 4 for Numbat), HT268B1 (10 for CalicoST and 39 for Numbat), HT270P1 (2 for CalicoST and 12 for Numbat), HT288P1 (2 for CalicoST and 6 for Numbat), HT306P1 (2 for CalicoST and 5 for Numbat). The upper and lower bounds of the box denote the 25% and 75% quantiles, the center line denotes the median, and the lower (upper) whiskers denote the smallest (largest) value within 1.5 times the IQR (interquartile range).

Article Snippet: We applied CalicoST to infer allele-specific copy numbers on 10x Genomics Visium Spatial Transcriptomics data from 12 patients (26 slices) in HTAN (WashU cohort) across three cancer types (‘Running CalicoST on SRT data’).

Techniques: Clone Assay

Journal: Nature Methods

Article Title: Inferring allele-specific copy number aberrations and tumor phylogeography from spatially resolved transcriptomics

doi: 10.1038/s41592-024-02438-9

Figure Lengend Snippet: a , Spatial distribution and phylogeographic tree of three cancer clones inferred by CalicoST in two adjacent slices from patient HT112C1 with CRC liver metastasis. The grayscale indicates the inferred proportion of normal cells within each spot. Diamonds are the spatial centroid of each clone or inferred ancestor, and arrows indicate the inferred directions of tumor development. The distance between two slices in the z -coordinate is enlarged for clearer visualization. b , Allele-specific copy number profiles for the three cancer clones and the corresponding phylogeny (right) with branches in the phylogeny labeled by the number of unique large LOH events that occur on the branch. c , Spatial distribution and phylogeographic tree of two cancer clones inferred by CalicoST in five adjacent slices from patient HT268C1 with breast cancer. Color scheme is the same as a . d , Inferred allele-specific copy numbers and tumor phylogeny.

Article Snippet: We applied CalicoST to infer allele-specific copy numbers on 10x Genomics Visium Spatial Transcriptomics data from 12 patients (26 slices) in HTAN (WashU cohort) across three cancer types (‘Running CalicoST on SRT data’).

Techniques: Clone Assay, Labeling

Journal: Nature Methods

Article Title: Inferring allele-specific copy number aberrations and tumor phylogeography from spatially resolved transcriptomics

doi: 10.1038/s41592-024-02438-9

Figure Lengend Snippet: a , Spatial distribution of cancer clones inferred jointly by CalicoST across five slices from a cancerous prostate. Positioning of five slices is according to ref. . Colors indicate inferred clones, including the normal clone in gray. Arrows represent the phylogeography of tumor evolution. b , Allele-specific copy number profiles for the five cancer clones and the corresponding phylogeny with branches in the phylogeny labeled by the number of unique large LOH events that occur on the branch. Colors indicate allele-specific copy numbers. The orientation and position of triangles indicate mirrored CNA events. c , BAF of each clone in chr6 and chr8. Colors indicate allele-specific copy numbers using the same color scheme as in b .

Article Snippet: We applied CalicoST to infer allele-specific copy numbers on 10x Genomics Visium Spatial Transcriptomics data from 12 patients (26 slices) in HTAN (WashU cohort) across three cancer types (‘Running CalicoST on SRT data’).

Techniques: Clone Assay, Labeling

Journal: Nature Methods

Article Title: Inferring allele-specific copy number aberrations and tumor phylogeography from spatially resolved transcriptomics

doi: 10.1038/s41592-024-02438-9

Figure Lengend Snippet: ( a ) UMAP of gene expression in spots from five slices of a multi-section prostate cancer patient (without applying any batch effect correction or integration tools). Each point represents a spot, colored by the slice location. ( b ) UMAP of gene expression from five slices, with each spot (point) colored according to the clone assignment from CalicoST. Grayscale indicates the inferred tumor proportion, with more gray representing a higher proportion of normal cells. ( c ) BAF along the genome for spots assigned to clone 5 from three slices (H1 4, H1 5, and H2 5) from the right portion of the prostate. Each point represents a genomic bin, colored by the inferred allele-specific copy numbers from CalicoST.

Article Snippet: We applied CalicoST to infer allele-specific copy numbers on 10x Genomics Visium Spatial Transcriptomics data from 12 patients (26 slices) in HTAN (WashU cohort) across three cancer types (‘Running CalicoST on SRT data’).

Techniques: Gene Expression

Journal: Nature Methods

Article Title: Inferring allele-specific copy number aberrations and tumor phylogeography from spatially resolved transcriptomics

doi: 10.1038/s41592-024-02438-9

Figure Lengend Snippet: Each spot is colored by the clone inferred by CalicoST, with gray indicating normal spots. Spots containing the variant allele of the somatic SNV are marked by a black cross. Spots containing the reference allele are marked by a gray circle. The first five SNVs are inferred to be truncal SNVs present in both the left and right sides of the prostate, while the sixth SNV (bottom right) is inferred to be present in only the left side.

Article Snippet: We applied CalicoST to infer allele-specific copy numbers on 10x Genomics Visium Spatial Transcriptomics data from 12 patients (26 slices) in HTAN (WashU cohort) across three cancer types (‘Running CalicoST on SRT data’).

Techniques: Variant Assay

Journal: Nature Methods

Article Title: Inferring allele-specific copy number aberrations and tumor phylogeography from spatially resolved transcriptomics

doi: 10.1038/s41592-024-02438-9

Figure Lengend Snippet: ( a ) Spatial organization of normal (clone 0) and three tumor clones (clones 1-3) inferred by CalicoST on a human melanoma sample sequenced using Slide-tags. ( b ) Compar- ison of cell type labels for each location from and clone labels inferred by CalicoST. ( c ) Allele-specific copy numbers inferred by CalicoST for each clone. ( d ) RDR and BAF along the genome for clones 1 and 2. Colors indicate the allele-specific copy number of the corresponding genomic bin. Red box highlights a LOH event on chr3q that is unique to clone 2.

Article Snippet: We applied CalicoST to infer allele-specific copy numbers on 10x Genomics Visium Spatial Transcriptomics data from 12 patients (26 slices) in HTAN (WashU cohort) across three cancer types (‘Running CalicoST on SRT data’).

Techniques: Clone Assay