.. Seeqx API documentation .. toctree:: :hidden: Why Seeq API? User Guide Seeq Entities Seeq Knowledge Graph API Documentation ----------------- Seeq API is a comprehensive data API that allows you to focus on building your genomic analysis workflow without having to manage various databases, bioinformatics tools, and compute clusters. This allows you to build pipelines that can run on any device, where your data resides. Seeq API is also the knowledge engine behind our search engine `seeq.bio `_ which you can use to get a sense for Seeq API can do. To learn more about why we built this, see :ref:`Why Seeq API?` Getting Started =============== To get started with Seeq API, see the :ref:`User Guide` and `API Reference `_. You can also quickly get your hands dirty with a `live interactive `_ version. How does it work? ================= Seeq API accepts predictable resource-oriented URLs and returns JSON-encoded responses with standard HTTP response codes. To use it, all you need is an HTTP client. This could be your web browser, `curl `_, or the standard library in your programming language of choice. The foundation of Seeq API is its :ref:`core entities`: genes, variants, diseases, drugs, proteins, etc. Each core entity has a unified, comprehensive annotation in Seeq API. For example see user guide sections on annotation for :ref:`genes`, :ref:`variants`, and :ref:`drugs`. The real power of Seeq API is in its continuously evolving :ref:`knowledge graph`. The knowledge graph allows you to extract connections between various entities instantly, with evidence backed by the latest peer-reviewed publications and clinical databases. built from thousands of publications and public datasets. The knowledge graph consists of multiple distinct graphs, each representing a specific semantic relationship between two or more core entities. Most importantly the knowledge graph is capable of :ref:`slicing and minifying` itself, allowing data analysis to happen where data resides, without having to shuffle data back and forth across data centers, compute clusters, and possibly across jurisdictions.