Harmonize in-house and public single-cell ATAC-seq datasets to ML-ready formats and leverage a suite of custom solutions designed for single-cell data, to accelerate analysis and insight generation.
Eliminate the need to find, download, and annotate individual scATAC-seq datasets.
Rich metadata for advanced epigenomics research.
Analysis-ready datasets with comprehensive quality metrics.
Easily uncover single-cell heterogeneity during development, differentiation, and disease.
Push discovery boundaries with custom-curated scATAC-seq datasets.
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Leverage a personalized atlas of expertly curated scATAC-seq datasets collected from diverse public sources and tailored to your research needs.
Support ingestion of multiple assay types - standalone scATAC-seq and multi-modal scATAC + RNA-seq assays while managing multi-sample aggregation through peak harmonization with CellRanger or Signac.
Accelerate your analysis with high-quality, analysis-ready scATAC-seq data.
Benefit from multiple QC metrics (nucleosome signal, fragment counts, TSS enrichment, fragment length distributions) that provide a thorough measure of data quality.
Integrate scATAC with other omics data types (e.g., transcriptomics, genomics) to gain a more comprehensive understanding of cellular processes.
We harmonize unstructured ATAC-seq data with a configurable, transparent, and granular curation process.
Flexible and transparent curation process, meticulously managing metadata at every level—dataset, sample, and feature level using internationally recognized ontologies.
Each dataset includes quality verification reports with common QC metrics and plots for detailed data evaluation.
Leverage our expertise to construct custom applications, unique to your research.
Our built-in visualization app features interactive exploration and analysis of scATAC-seq datasets directly on Atlas. Use APIs or GUI to stream harmonized data on external tools like Spotfire, or your preferred analysis environment like react, Shiny, etc.
Work with our experts to build or customize a production-ready, scientifically validated application that caters to your research needs.
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Request extra metadata fields, use custom ontologies, or annotate cell types with your preferred marker database.
Consistently process, annotate, and QC single-cell data using scientifically validated Polly pipelines to ensure data interoperability.
Seamlessly integrate Polly into your existing infrastructure! Automate ingestion of in-house data from your data storage (ELN, S3 bucket, CROs, and more) into a central Atlas on Polly.
Focus on discovery, not data wrangling! Polly automatically cleans, harmonizes, and structures your in-house single-cell datasets, ensuring they adhere to your custom schema.
Integrate multi-modal datasets into one central Atlas to unveil hidden patterns, and expedite research breakthroughs.
Effortlessly manage and analyze TBs of both in-house and public single-cell data on Polly's secure cloud.
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All single-cell datasets delivered by Polly undergo ~50 QA checks to ensure quality and provenance.
Assess the intrinsic quality of the data (genes, cells, measurements) with comprehensive QA reports detailing the processing methodology.
Avail unrestricted data connectivity and consumption between Polly and your preferred analysis environments. Use APIs to stream harmonized data on Polly to external tools and applications.
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Annotate distinct cell types and rare cell populations based on differential gene expression and chromatin accessibility by combining scATAC and RNA-seq datasets. Identify cell-type specific transcription factors using scATAC-seq powered motif analyses.
Gain insights into cell fate determination by identifying cell type-specific epigenetic regulatory elements. Chart chromatin accessibility dynamics during differentiation using scATAC-seq based trajectory analyses.
Explore disease-specific alterations in chromatin accessibility. Prioritize disease-critical regulatory elements by integration with additional modalities like GWAS.
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Our ATAC-seq datasets come with comprehensive quality metrics and rich metadata, designed to enhance your epigenomics research. Dive deep into the mechanisms of single-cell heterogeneity across development, differentiation, and disease.
Data processing and scientific reporting of metabolomics data are crucial but also tedious. Polly’s range of applications helped our team in accelerating these processes significantly and effectively.
Extremely impressed by Polly and its power to digest and integrate large datasets. The unique partnership that we have allows us to work hand-in-hand with software engineers and scientists to rapidly develop novel hypotheses that we can test in the lab.
We really were pleasantly surprised because this tool [El-MAVEN] is really useful in fast analysis of tracer data. It allows us to really look at a broad set of targets so you are not limited anymore for data analysis. A data analyst of mine stepped up to me and said, "I can do now in 3 hours what used to take 4 days.
Data analysis is the biggest bottleneck for metabolomics research. Elucidata has worked directly with us to streamline our analysis pipeline, accelerating the pace of our research.
We were looking for public data on a tight deadline to make decisions on our back up targets for solid tumors. Elucidata was able to understand our relevance criteria, identify, and deliver high-quality harmonized data ahead of schedule. We are really happy with their deliveries and this partnership.
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