Resource guide

Guide

Learn how to browse the atlas, interpret a virtual spatial map, run prediction on your own H&E image, and report the outputs responsibly.

01

Browse the atlas

The atlas contains 6,021 indexed TCGA whole-slide predictions across BRCA, SKCM, and COAD/READ.

  1. Search or filter

    Use a cohort name, case ID, slide ID, or gene keyword. Filters can restrict the table by cohort, spatial-map availability, H&E availability, and tile count.

  2. Open one slide

    Select a slide ID in the table to enter its interactive record. The default order groups BRCA, SKCM, and COAD/READ and ranks slides by tissue-tile count within each cohort.

  3. Export the current view

    Use Export Current View to save the current filtered slide manifest for reproducible downstream selection.

Open Atlas
02

Read a virtual spatial map

Slide Detail combines the H&E thumbnail with tile-level HistoOmniST predictions.

  1. Choose a feature

    Select a gene or spatial program from the control bar. The map redraws the selected virtual signal without changing the underlying H&E image.

  2. Adjust point size

    Point size changes only the display. Hover over a point to read its tile coordinates, predicted value, and tissue fraction.

  3. Read the color scale

    Colors are scaled within each slide, usually after percentile clipping. Use them to inspect within-slide spatial patterns, not to compare absolute intensity between slides.

03

Run prediction on your image

The upload workflow accepts SVS, TIFF, PNG, and JPG images and stores each submission in a private job workspace.

  1. Select an image

    Upload one or more H&E images. The default dense mode is intended for formal spatial-map inspection.

  2. Review advanced settings only when needed

    Target spots, spot limit, and minimum stride control spatial sampling density and runtime. They do not change the trained model parameters.

  3. Open the completed result

    The result page provides an H&E thumbnail, interactive gene and program maps, state maps, prediction tables, an integrated report, and a download package.

Open Upload Prediction
04

Understand the outputs

The website exposes model-derived virtual signals at tile or spot resolution.

OutputMeaningRecommended use
gene_*Count-log1p virtual expression reconstructed from rate and mean-one predicted SFWithin-slide gene-pattern inspection
count_*Count-scale virtual signal reconstructed with predicted SFCount-scale analyses with the stated model version
pred_sfPredicted slide-normalized size factorRate-to-count reconstruction and QC
program_*Predicted spatial-program scoreInspect epithelial, stromal, immune, and proliferation patterns
state mapTile state assigned from predicted program profilesSummarize recurrent tissue states
05

Interpret results responsibly

Virtual spatial transcriptomes are computational predictions and must be reported with their validation scope.

No paired TCGA ST truth

TCGA maps are model-derived signals, not measured spot-level spatial transcriptomes.

Tissue-dependent performance

HEST validation shows stronger and weaker tissues. Do not generalize a strong organ result to every tissue.

Associations are not clinical models

Survival and molecular associations support biological relevance but are not deployed diagnostic or treatment-decision systems.

06

Privacy, citation, and reuse

Uploaded jobs and downloaded predictions require clear provenance and responsible handling.

Operational access logs

For security, abuse prevention, and service reliability, the server records source IP, request time, path without query parameters, status code, request duration, and browser identifier. Raw logs are retained for 10 days and are not published as atlas data.

Private jobs

Uploaded jobs are accessed through a private URL or browser-stored token. Public pages do not list other users' submissions.

Citation

Cite HistoOmniST and the original cohort or validation dataset. Describe downloaded values as model-derived virtual spatial transcriptome signals.

Minimum reporting

Report the model version, cohort, slide ID, selected gene or program, spatial sampling settings, and color-scale convention.