Rat Genome Database

The Rat Genome Database (RGD) was established in 1999 and is the premier site for genetic, genomic, phenotype, and disease data generated from rat research

Integrate the Rat Genome Database API with the Python API

Setup the Rat Genome Database API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Rat Genome Database and Python remarkably fast. Free for developers.

Run Python Code with the Python API

Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.

 
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Overview of Rat Genome Database

The Rat Genome Database (RGD) API provides access to a wealth of genetic and genomic data related to rats, a key model organism in medical research. Via this API, researchers can query for gene information, phenotypic data, and genomic sequences, creating a treasure trove for geneticists, bioinformaticians, and medical researchers seeking to understand disease pathways and potential treatments. On Pipedream, this can be leveraged to automate data retrieval, sync genetic information with other databases, or trigger workflows based on specific genomic updates or criteria.

Connect Rat Genome Database

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    rat_genome_database: {
      type: "app",
      app: "rat_genome_database",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://rest.rgd.mcw.edu/rgdws/lookup/geneTypes`,
      headers: {
        "Accept": `*/*`,
      },
    })
  },
})

Overview of Python

Develop, run and deploy your Python code in Pipedream workflows. Integrate seamlessly between no-code steps, with connected accounts, or integrate Data Stores and manipulate files within a workflow.

This includes installing PyPI packages, within your code without having to manage a requirements.txt file or running pip.

Below is an example of using Python to access data from the trigger of the workflow, and sharing it with subsequent workflow steps:

Connect Python

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def handler(pd: "pipedream"):
  # Reference data from previous steps
  print(pd.steps["trigger"]["context"]["id"])
  # Return data for use in future steps
  return {"foo": {"test":True}}