Spatial Transcriptomics Data on Polly

Unlock the power of spatial transcriptomics with ML-ready data ingested from public databases or your in-house assays. Identify spatially regulated genes and gain deeper insights into disease mechanisms.


Polly Harmonizes Spatial Transcriptomics Data for Enhanced Insights Into Gene Expression Patterns

Transform Your Understanding of Complex Biology with Harmonized Spatial Transcriptomics Data

Configure Curation to Fit Your Analysis Needs

Polly harmonizes Spatial Transcriptomics (SRT) data from diverse public and in-house sources by integrating raw counts matrix, spatial coordinates, imaging data, and metadata seamlessly.

Use Polly’s Validated Custom Pipelines for Consistent Processing

Access unfiltered raw counts from original publications and get consistently processed spatial transcriptomics data to replicate author-defined counts.

Explore Rich Metadata Annotations on Polly

Access spatial datasets with deeply annotated metadata up to 3 levels (dataset, sample, and feature) for in-depth analysis.

Expert QC to Ensure Pristine Data Quality

Every spatial transcriptomics dataset on Polly goes through ~50 QA/QC checks for metadata quality, filtering and normalization, batch effect correction, and quality of measurements.

Centralize Data on Polly for Effortless Querying and Analysis

Integrate spatial transcriptomics datasets into one central Atlas to unveil cell-type localization patterns, and expedite research breakthroughs.

Ready-to-use ETL Pipelines

Streamline QC filtering, normalization, clustering, and spatial variable gene analysis with deconvolution for comprehensive insights.

Unified Storage Architecture

Polly’s ‘Unified Data Model’ stores diverse datasets within a single relational database, optimizing storage efficiency.

API-powered Accessibility

Enable seamless access and queries on top of high-quality harmonized and integrated data with APIs.

Revealing Spatial Gene Networks with  ML Solutions for Coordinated Expression Analysis

Advance research with harmonized spatial datasets with confidence using Polly’s extensive suite of ML solutions.

Unlock the Symphony of Genes in Tissues with Spatial Co-expression Network Analysis

Harness cutting-edge graph-based ML algorithms to unveil spatially coordinated gene expression, decoding the language of regulatory networks.

Elevate Your Analysis with Spatially Informed Feature Selection

Enhance analysis by integrating spatial information into feature selection. Deploy informed variable selection or clustering algorithms to identify genes or features linked with specific spatial patterns or cell types.

Analyze and Visualize Spatial Transcriptomics  Data on Polly

Build Custom Dashboards

Leverage custom applications and dashboards to visualize cell-type composition, empowering in-depth exploration and interpretation of trends and patterns.

Visualize Harmonized Data Using CellxGene VIP

Use native web-apps integrated on Polly - like CellxGene VIP to analyze and visualize an array of spatial transcriptomics data on the fly.

Polly Verified – Our Quality Guarantee

We use ~50 QA Checks to ensure every dataset is:


Data validation checks ensure that all cell & dataset-level metadata annotations contain non-NULL and non-blank values.


Rigorous QC checks to ensure metadata attributes are human-readable and accurately assigned at all levels (dataset, cell).


Normalization & Batch Effect correction are applied wherever necessary to eliminate technical variations and enable meaningful comparisons between cells.


Doublets, which can arise during sample preparation and confound analysis, are identified and removed.


Poor quality cells and genes are filtered out. We also identify highly variable genes that drive biological variation and use them for downstream analyses, improving the robustness of results.


Deciphering Gene Expression in 3D with Spatial Transcriptomics

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