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Use production-ready bioinformatics pipelines deployed on an infrastructure of your choice.
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Pick from a suite of scientifically validated bioinformatics pipelines to process a host of multi-omics data types.
Use our expertise to develop and deploy customized pipelines tailored to your omics data type & analysis requirements.
Work with Polly’s fully managed infrastructure to process & analyze large datasets in a cost-effective manner. Reduce dependencies on your local environment & auto-scale resources based on usage.
Select computational resources, docker environments, or machine types as per the complexity of your jobs.
Run complex, multi-threaded pipelines with Polly’s NextFlow integrations. Reduce time taken to process high throughput data by 50%.
Ingest, transform, and curate data at scale with Polly's harmonization engine. Automate your data flow to increase throughput & speed.
Orchestrate identifier mapping, quality checks, and a whole gamut of data pre-processing steps.
Automatically map processed datasets critical metadata and enforce a schema.
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A bioinformatics pipeline is a series of computational steps designed to process and analyze biological data, transforming raw inputs into meaningful insights.
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In genome sequencing, pipelines automate tasks such as read alignment, variant calling, and annotation, ensuring efficient and accurate data interpretation.
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Building a bioinformatics pipeline involves selecting appropriate tools, integrating them into a cohesive workflow, and validating the process to ensure reliable results.
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Key components of a bioinformatics pipeline include data preprocessing, alignment, analysis, and visualization modules.
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In bioinformatics, a 'pipeline' refers to a predefined, linear sequence of processes, whereas a 'workflow' may encompass a more flexible, possibly non-linear arrangement of tasks.
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The term 'process' generally denotes a single computational task, while a 'pipeline' refers to a connected series of such processes working together to analyze data.
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