Utilize consistently processed, ML-ready in-house and public Bulk RNA-seq datasets on Polly. Ideal for meta-analysis, rare transcript discovery, and integrative multi-omics analysis.
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Polly harmonizes unstructured bulk RNA-seq data with a configurable, transparent, and granular curation process as per your inclusion/ exclusion criteria to accelerate downstream analysis.
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Polly’s datasets come with 99.99% accuracy and have ontology-backed metadata for 30+ fields.
Polly delivers bulk RNA-seq datasets with 100% metadata completeness and 0 empty metadata fields.
Polly makes bulk RNA-seq data from disparate sources interoperable & analysis-ready by delivering it in consistent formats, usable by both Python and R users.
Work with ready-to-use ETL pipelines for processing bulk RNA-seq data on Polly, or build custom pipelines fit for your data and analysis requirements.
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Work with your bulk RNA-seq data on flexible pipelines based on STAR and Kallisto for alignment/mapping available on Polly.
Utilize our experience to create additional pipelines that provide modular options for QC tools, feature counting tools, aligners, and annotation that can be built on demand.
Use Polly to do QC over sequencing data and metadata for harmonization. Adjust alignment/mapping, QC, feature counting, and other step parameters and annotations fit for your research.
Extract deeper insights from data at hand by using Polly’s extensive suite of ML solutions to accelerate downstream analysis.
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Work with our experts to deploy deploy foundational ML models on top of your own harmonized bulk RNA-seq data.
Perform gene, pathway, or metadata-based queries to find and explore the data you need for downstream solutions like predicting biomarkers, identifying target, meta-analysis and more. Utilize interactive volcano plots, heatmaps, and more to visualize enriched genes and pathways.
Develop methods for integrating bulk RNA-seq data with other omics data types (e.g., genomics, proteomics) to gain a more comprehensive understanding of cellular processes.
Use native web-apps integrated on Polly- like Phantasus to analyze and visualize an array of bulk RNA-seq data on the fly.
Use Polly’s APIs or GUI to stream harmonized data on external tools, applications like Spotfire, or your preferred analysis environment like react, shiny, etc., to avail unrestricted consumption.
Work with our experts to build or customize a production-ready, scientifically validated application that caters to your research needs.
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Tailor your research with flexible bioinformatics pipelines like STAR, Kallisto, and more, on Polly, achieving consistent, cost-effective data processing.
Customize the QC mechanisms, cut-offs, and log-fold thresholds used to guarantee superior data quality throughout the ETL process.
Request additional curation of metadata, cohorts, or comparisons within cohorts to streamline the search for biologically relevant signatures.
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’s AI-assisted curation automatically harmonizes all your data into ML-ready formats, in a fraction of the time.
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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Our experts implement ~50 QA checks to perform batch effect correction, metadata validation, and remove technical artifacts & variations in every dataset.
The data normalization methods or QC metrics used on Polly are not a black box. Learn how each Bulk RNA-seq dataset was processed by downloading a detailed QA/QC report from Polly.
Perform gene, pathway, or metadata-based queries to find and explore the data you need.
Utilize interactive volcano plots, heatmaps, and more to visualize enriched genes and pathways.
Stream Polly harmonized Bulk RNA-seq datasets to your preferred tools for advanced analyses.
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We use at least ~50 QA Checks to ensure every dataset is:
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Data validation checks ensure that all cell & dataset-level metadata annotations contain non-NULL and non-blank values, all metadata attributes are human-readable and accurately assigned at all levels.
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Normalization & Batch Effect correction are applied wherever necessary to eliminate technical variations and enable meaningful comparisons between cells.
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Polly filters out poor-quality cells and genes and also identifies highly variable genes that drive biological variation useful for downstream analyses, and for improving the robustness of results.
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Bulk RNA-Seq Datasets on Polly represent a curated collection of biologically and statistically comparable samples. All the datasets are denoted using a unique ID, which follows the GEO record identifier format comprising a series ID and a platform ID. For example, dataset ID 'GSE189190_GPL25947_raw’ would translate to:
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We offer 30+ curated fields for bulk RNA-seq datasets on Polly. If any additional curated fields are required, they are added on request as part of custom curation. There are 6 standard fields mapped to ontologies at dataset and sample level:
Disease → MeSH
Tissue → BRENDA Tissue Ontology
Organism → NCBI Taxonomy
Cell Line → Cellosaurus
Cell type → Cell Ontology
Drug → PubChem
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Bulk RNA-seq datasets are stored in the GCT format on Polly. Additionally, our team can also support custom requests for providing data in the file formats that are best suited for the downstream bioinformatics tools and pipelines used by our clients.
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Bulk RNA-seq data on Polly has various benefits,
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Bulk RNA-seq data from FastQ files can be processed using either of the following options:
The data is processed with the following reference genome, annotation, and complementary DNA sequence data from Ensembl release 107 for each organism.
We provide Kallisto and STAR as the default choices for processing Bulk RNA-seq data. However, customizations in the normalization steps, QC metrics used, and so on can be made to these pipelines at an additional cost.
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Yes, our team has the expertise to help with horizontal (within omics) or vertical (across omics) integration as a part of Polly enabled solutions. The choice of integration method is dependent on the biological question and downstream analysis and is mutually finalised with clients.
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